lithium0003's picture
add file
015337e verified
program(1.0)
[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3304.5.2"}, {"coremlc-version", "3304.6.2"}, {"coremltools-component-torch", "2.2.2"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "7.2"}})]
{
func main<ios17>(tensor<fp16, [1, 80, 3000]> logmel_data) {
tensor<int32, []> var_32 = const()[name = tensor<string, []>("op_32"), val = tensor<int32, []>(1)];
tensor<int32, [1]> var_40 = const()[name = tensor<string, []>("op_40"), val = tensor<int32, [1]>([1])];
tensor<int32, [1]> var_42 = const()[name = tensor<string, []>("op_42"), val = tensor<int32, [1]>([1])];
tensor<string, []> var_44_pad_type_0 = const()[name = tensor<string, []>("op_44_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> var_44_pad_0 = const()[name = tensor<string, []>("op_44_pad_0"), val = tensor<int32, [2]>([1, 1])];
tensor<fp16, [768, 80, 3]> weight_3_to_fp16 = const()[name = tensor<string, []>("weight_3_to_fp16"), val = tensor<fp16, [768, 80, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))];
tensor<fp16, [768]> bias_3_to_fp16 = const()[name = tensor<string, []>("bias_3_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(368768)))];
tensor<fp16, [1, 768, 3000]> var_44_cast_fp16 = conv(bias = bias_3_to_fp16, dilations = var_42, groups = var_32, pad = var_44_pad_0, pad_type = var_44_pad_type_0, strides = var_40, weight = weight_3_to_fp16, x = logmel_data)[name = tensor<string, []>("op_44_cast_fp16")];
tensor<string, []> input_1_mode_0 = const()[name = tensor<string, []>("input_1_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 768, 3000]> input_1_cast_fp16 = gelu(mode = input_1_mode_0, x = var_44_cast_fp16)[name = tensor<string, []>("input_1_cast_fp16")];
tensor<int32, []> var_49 = const()[name = tensor<string, []>("op_49"), val = tensor<int32, []>(1)];
tensor<int32, [1]> var_58 = const()[name = tensor<string, []>("op_58"), val = tensor<int32, [1]>([2])];
tensor<int32, [1]> var_60 = const()[name = tensor<string, []>("op_60"), val = tensor<int32, [1]>([1])];
tensor<string, []> var_62_pad_type_0 = const()[name = tensor<string, []>("op_62_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [2]> var_62_pad_0 = const()[name = tensor<string, []>("op_62_pad_0"), val = tensor<int32, [2]>([1, 1])];
tensor<fp16, [768, 768, 3]> weight_7_to_fp16 = const()[name = tensor<string, []>("weight_7_to_fp16"), val = tensor<fp16, [768, 768, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(370368)))];
tensor<fp16, [768]> bias_7_to_fp16 = const()[name = tensor<string, []>("bias_7_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3909376)))];
tensor<fp16, [1, 768, 1500]> var_62_cast_fp16 = conv(bias = bias_7_to_fp16, dilations = var_60, groups = var_49, pad = var_62_pad_0, pad_type = var_62_pad_type_0, strides = var_58, weight = weight_7_to_fp16, x = input_1_cast_fp16)[name = tensor<string, []>("op_62_cast_fp16")];
tensor<string, []> x_3_mode_0 = const()[name = tensor<string, []>("x_3_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 768, 1500]> x_3_cast_fp16 = gelu(mode = x_3_mode_0, x = var_62_cast_fp16)[name = tensor<string, []>("x_3_cast_fp16")];
tensor<int32, [3]> var_68 = const()[name = tensor<string, []>("op_68"), val = tensor<int32, [3]>([0, 2, 1])];
tensor<fp16, [1500, 768]> positional_embedding_to_fp16 = const()[name = tensor<string, []>("positional_embedding_to_fp16"), val = tensor<fp16, [1500, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3910976)))];
tensor<fp16, [1, 1500, 768]> transpose_120 = transpose(perm = var_68, x = x_3_cast_fp16)[name = tensor<string, []>("transpose_120")];
tensor<fp16, [1, 1500, 768]> var_71_cast_fp16 = add(x = transpose_120, y = positional_embedding_to_fp16)[name = tensor<string, []>("op_71_cast_fp16")];
tensor<int32, []> var_84 = const()[name = tensor<string, []>("op_84"), val = tensor<int32, []>(-1)];
tensor<int32, [1]> var_100_axes_0 = const()[name = tensor<string, []>("op_100_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_0_attn_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_0_attn_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6215040)))];
tensor<fp16, [768]> blocks_0_attn_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_0_attn_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6216640)))];
tensor<fp16, []> var_90_to_fp16 = const()[name = tensor<string, []>("op_90_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
tensor<fp16, [1, 1500, 768]> var_100_cast_fp16 = layer_norm(axes = var_100_axes_0, beta = blocks_0_attn_ln_bias_to_fp16, epsilon = var_90_to_fp16, gamma = blocks_0_attn_ln_weight_to_fp16, x = var_71_cast_fp16)[name = tensor<string, []>("op_100_cast_fp16")];
tensor<fp16, [768, 768]> var_111_to_fp16 = const()[name = tensor<string, []>("op_111_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6218240)))];
tensor<fp16, [768]> var_112_to_fp16 = const()[name = tensor<string, []>("op_112_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7397952)))];
tensor<fp16, [1, 1500, 768]> linear_0_cast_fp16 = linear(bias = var_112_to_fp16, weight = var_111_to_fp16, x = var_100_cast_fp16)[name = tensor<string, []>("linear_0_cast_fp16")];
tensor<fp16, [768, 768]> var_115_to_fp16 = const()[name = tensor<string, []>("op_115_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7399552)))];
tensor<fp16, [768]> linear_1_bias_0_to_fp16 = const()[name = tensor<string, []>("linear_1_bias_0_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8579264)))];
tensor<fp16, [1, 1500, 768]> linear_1_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = var_115_to_fp16, x = var_100_cast_fp16)[name = tensor<string, []>("linear_1_cast_fp16")];
tensor<fp16, [768, 768]> var_119_to_fp16 = const()[name = tensor<string, []>("op_119_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8580864)))];
tensor<fp16, [768]> var_120_to_fp16 = const()[name = tensor<string, []>("op_120_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9760576)))];
tensor<fp16, [1, 1500, 768]> linear_2_cast_fp16 = linear(bias = var_120_to_fp16, weight = var_119_to_fp16, x = var_100_cast_fp16)[name = tensor<string, []>("linear_2_cast_fp16")];
tensor<int32, [4]> var_128 = const()[name = tensor<string, []>("op_128"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_129_cast_fp16 = reshape(shape = var_128, x = linear_0_cast_fp16)[name = tensor<string, []>("op_129_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_84_to_fp16 = const()[name = tensor<string, []>("const_84_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> q_3_cast_fp16 = mul(x = var_129_cast_fp16, y = const_84_to_fp16)[name = tensor<string, []>("q_3_cast_fp16")];
tensor<int32, [4]> var_135 = const()[name = tensor<string, []>("op_135"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_136_cast_fp16 = reshape(shape = var_135, x = linear_1_cast_fp16)[name = tensor<string, []>("op_136_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_85_to_fp16 = const()[name = tensor<string, []>("const_85_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> k_3_cast_fp16 = mul(x = var_136_cast_fp16, y = const_85_to_fp16)[name = tensor<string, []>("k_3_cast_fp16")];
tensor<int32, [4]> var_142 = const()[name = tensor<string, []>("op_142"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_143_cast_fp16 = reshape(shape = var_142, x = linear_2_cast_fp16)[name = tensor<string, []>("op_143_cast_fp16")];
tensor<int32, [4]> var_144 = const()[name = tensor<string, []>("op_144"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<bool, []> qk_1_transpose_x_0 = const()[name = tensor<string, []>("qk_1_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> qk_1_transpose_y_0 = const()[name = tensor<string, []>("qk_1_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<int32, [4]> transpose_48_perm_0 = const()[name = tensor<string, []>("transpose_48_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
tensor<int32, [4]> transpose_49_perm_0 = const()[name = tensor<string, []>("transpose_49_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
tensor<fp16, [1, 12, 64, 1500]> transpose_117 = transpose(perm = transpose_49_perm_0, x = k_3_cast_fp16)[name = tensor<string, []>("transpose_117")];
tensor<fp16, [1, 12, 1500, 64]> transpose_118 = transpose(perm = transpose_48_perm_0, x = q_3_cast_fp16)[name = tensor<string, []>("transpose_118")];
tensor<fp16, [1, 12, 1500, 1500]> qk_1_cast_fp16 = matmul(transpose_x = qk_1_transpose_x_0, transpose_y = qk_1_transpose_y_0, x = transpose_118, y = transpose_117)[name = tensor<string, []>("qk_1_cast_fp16")];
tensor<fp16, [1, 12, 1500, 1500]> var_148_cast_fp16 = softmax(axis = var_84, x = qk_1_cast_fp16)[name = tensor<string, []>("op_148_cast_fp16")];
tensor<bool, []> var_150_transpose_x_0 = const()[name = tensor<string, []>("op_150_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> var_150_transpose_y_0 = const()[name = tensor<string, []>("op_150_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [1, 12, 1500, 64]> transpose_119 = transpose(perm = var_144, x = var_143_cast_fp16)[name = tensor<string, []>("transpose_119")];
tensor<fp16, [1, 12, 1500, 64]> var_150_cast_fp16 = matmul(transpose_x = var_150_transpose_x_0, transpose_y = var_150_transpose_y_0, x = var_148_cast_fp16, y = transpose_119)[name = tensor<string, []>("op_150_cast_fp16")];
tensor<int32, [4]> var_151 = const()[name = tensor<string, []>("op_151"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> concat_0 = const()[name = tensor<string, []>("concat_0"), val = tensor<int32, [3]>([1, 1500, 768])];
tensor<fp16, [1, 1500, 12, 64]> transpose_116 = transpose(perm = var_151, x = var_150_cast_fp16)[name = tensor<string, []>("transpose_116")];
tensor<fp16, [1, 1500, 768]> x_11_cast_fp16 = reshape(shape = concat_0, x = transpose_116)[name = tensor<string, []>("x_11_cast_fp16")];
tensor<fp16, [768, 768]> var_156_to_fp16 = const()[name = tensor<string, []>("op_156_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9762176)))];
tensor<fp16, [768]> var_157_to_fp16 = const()[name = tensor<string, []>("op_157_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10941888)))];
tensor<fp16, [1, 1500, 768]> linear_3_cast_fp16 = linear(bias = var_157_to_fp16, weight = var_156_to_fp16, x = x_11_cast_fp16)[name = tensor<string, []>("linear_3_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_13_cast_fp16 = add(x = var_71_cast_fp16, y = linear_3_cast_fp16)[name = tensor<string, []>("x_13_cast_fp16")];
tensor<int32, [1]> var_164_axes_0 = const()[name = tensor<string, []>("op_164_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_0_mlp_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_0_mlp_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10943488)))];
tensor<fp16, [768]> blocks_0_mlp_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_0_mlp_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10945088)))];
tensor<fp16, [1, 1500, 768]> var_164_cast_fp16 = layer_norm(axes = var_164_axes_0, beta = blocks_0_mlp_ln_bias_to_fp16, epsilon = var_90_to_fp16, gamma = blocks_0_mlp_ln_weight_to_fp16, x = x_13_cast_fp16)[name = tensor<string, []>("op_164_cast_fp16")];
tensor<fp16, [3072, 768]> var_173_to_fp16 = const()[name = tensor<string, []>("op_173_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10946688)))];
tensor<fp16, [3072]> var_174_to_fp16 = const()[name = tensor<string, []>("op_174_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15665344)))];
tensor<fp16, [1, 1500, 3072]> linear_4_cast_fp16 = linear(bias = var_174_to_fp16, weight = var_173_to_fp16, x = var_164_cast_fp16)[name = tensor<string, []>("linear_4_cast_fp16")];
tensor<string, []> x_17_mode_0 = const()[name = tensor<string, []>("x_17_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 1500, 3072]> x_17_cast_fp16 = gelu(mode = x_17_mode_0, x = linear_4_cast_fp16)[name = tensor<string, []>("x_17_cast_fp16")];
tensor<fp16, [768, 3072]> var_179_to_fp16 = const()[name = tensor<string, []>("op_179_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15671552)))];
tensor<fp16, [768]> var_180_to_fp16 = const()[name = tensor<string, []>("op_180_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(20390208)))];
tensor<fp16, [1, 1500, 768]> linear_5_cast_fp16 = linear(bias = var_180_to_fp16, weight = var_179_to_fp16, x = x_17_cast_fp16)[name = tensor<string, []>("linear_5_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_19_cast_fp16 = add(x = x_13_cast_fp16, y = linear_5_cast_fp16)[name = tensor<string, []>("x_19_cast_fp16")];
tensor<int32, []> var_190 = const()[name = tensor<string, []>("op_190"), val = tensor<int32, []>(-1)];
tensor<int32, [1]> var_206_axes_0 = const()[name = tensor<string, []>("op_206_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_1_attn_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_1_attn_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(20391808)))];
tensor<fp16, [768]> blocks_1_attn_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_1_attn_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(20393408)))];
tensor<fp16, []> var_196_to_fp16 = const()[name = tensor<string, []>("op_196_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
tensor<fp16, [1, 1500, 768]> var_206_cast_fp16 = layer_norm(axes = var_206_axes_0, beta = blocks_1_attn_ln_bias_to_fp16, epsilon = var_196_to_fp16, gamma = blocks_1_attn_ln_weight_to_fp16, x = x_19_cast_fp16)[name = tensor<string, []>("op_206_cast_fp16")];
tensor<fp16, [768, 768]> var_217_to_fp16 = const()[name = tensor<string, []>("op_217_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(20395008)))];
tensor<fp16, [768]> var_218_to_fp16 = const()[name = tensor<string, []>("op_218_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21574720)))];
tensor<fp16, [1, 1500, 768]> linear_6_cast_fp16 = linear(bias = var_218_to_fp16, weight = var_217_to_fp16, x = var_206_cast_fp16)[name = tensor<string, []>("linear_6_cast_fp16")];
tensor<fp16, [768, 768]> var_221_to_fp16 = const()[name = tensor<string, []>("op_221_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21576320)))];
tensor<fp16, [1, 1500, 768]> linear_7_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = var_221_to_fp16, x = var_206_cast_fp16)[name = tensor<string, []>("linear_7_cast_fp16")];
tensor<fp16, [768, 768]> var_225_to_fp16 = const()[name = tensor<string, []>("op_225_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22756032)))];
tensor<fp16, [768]> var_226_to_fp16 = const()[name = tensor<string, []>("op_226_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(23935744)))];
tensor<fp16, [1, 1500, 768]> linear_8_cast_fp16 = linear(bias = var_226_to_fp16, weight = var_225_to_fp16, x = var_206_cast_fp16)[name = tensor<string, []>("linear_8_cast_fp16")];
tensor<int32, [4]> var_234 = const()[name = tensor<string, []>("op_234"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_235_cast_fp16 = reshape(shape = var_234, x = linear_6_cast_fp16)[name = tensor<string, []>("op_235_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_86_to_fp16 = const()[name = tensor<string, []>("const_86_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> q_7_cast_fp16 = mul(x = var_235_cast_fp16, y = const_86_to_fp16)[name = tensor<string, []>("q_7_cast_fp16")];
tensor<int32, [4]> var_241 = const()[name = tensor<string, []>("op_241"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_242_cast_fp16 = reshape(shape = var_241, x = linear_7_cast_fp16)[name = tensor<string, []>("op_242_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_87_to_fp16 = const()[name = tensor<string, []>("const_87_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> k_7_cast_fp16 = mul(x = var_242_cast_fp16, y = const_87_to_fp16)[name = tensor<string, []>("k_7_cast_fp16")];
tensor<int32, [4]> var_248 = const()[name = tensor<string, []>("op_248"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_249_cast_fp16 = reshape(shape = var_248, x = linear_8_cast_fp16)[name = tensor<string, []>("op_249_cast_fp16")];
tensor<int32, [4]> var_250 = const()[name = tensor<string, []>("op_250"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<bool, []> qk_3_transpose_x_0 = const()[name = tensor<string, []>("qk_3_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> qk_3_transpose_y_0 = const()[name = tensor<string, []>("qk_3_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<int32, [4]> transpose_50_perm_0 = const()[name = tensor<string, []>("transpose_50_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
tensor<int32, [4]> transpose_51_perm_0 = const()[name = tensor<string, []>("transpose_51_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
tensor<fp16, [1, 12, 64, 1500]> transpose_113 = transpose(perm = transpose_51_perm_0, x = k_7_cast_fp16)[name = tensor<string, []>("transpose_113")];
tensor<fp16, [1, 12, 1500, 64]> transpose_114 = transpose(perm = transpose_50_perm_0, x = q_7_cast_fp16)[name = tensor<string, []>("transpose_114")];
tensor<fp16, [1, 12, 1500, 1500]> qk_3_cast_fp16 = matmul(transpose_x = qk_3_transpose_x_0, transpose_y = qk_3_transpose_y_0, x = transpose_114, y = transpose_113)[name = tensor<string, []>("qk_3_cast_fp16")];
tensor<fp16, [1, 12, 1500, 1500]> var_254_cast_fp16 = softmax(axis = var_190, x = qk_3_cast_fp16)[name = tensor<string, []>("op_254_cast_fp16")];
tensor<bool, []> var_256_transpose_x_0 = const()[name = tensor<string, []>("op_256_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> var_256_transpose_y_0 = const()[name = tensor<string, []>("op_256_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [1, 12, 1500, 64]> transpose_115 = transpose(perm = var_250, x = var_249_cast_fp16)[name = tensor<string, []>("transpose_115")];
tensor<fp16, [1, 12, 1500, 64]> var_256_cast_fp16 = matmul(transpose_x = var_256_transpose_x_0, transpose_y = var_256_transpose_y_0, x = var_254_cast_fp16, y = transpose_115)[name = tensor<string, []>("op_256_cast_fp16")];
tensor<int32, [4]> var_257 = const()[name = tensor<string, []>("op_257"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> concat_1 = const()[name = tensor<string, []>("concat_1"), val = tensor<int32, [3]>([1, 1500, 768])];
tensor<fp16, [1, 1500, 12, 64]> transpose_112 = transpose(perm = var_257, x = var_256_cast_fp16)[name = tensor<string, []>("transpose_112")];
tensor<fp16, [1, 1500, 768]> x_23_cast_fp16 = reshape(shape = concat_1, x = transpose_112)[name = tensor<string, []>("x_23_cast_fp16")];
tensor<fp16, [768, 768]> var_262_to_fp16 = const()[name = tensor<string, []>("op_262_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(23937344)))];
tensor<fp16, [768]> var_263_to_fp16 = const()[name = tensor<string, []>("op_263_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25117056)))];
tensor<fp16, [1, 1500, 768]> linear_9_cast_fp16 = linear(bias = var_263_to_fp16, weight = var_262_to_fp16, x = x_23_cast_fp16)[name = tensor<string, []>("linear_9_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_25_cast_fp16 = add(x = x_19_cast_fp16, y = linear_9_cast_fp16)[name = tensor<string, []>("x_25_cast_fp16")];
tensor<int32, [1]> var_270_axes_0 = const()[name = tensor<string, []>("op_270_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_1_mlp_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_1_mlp_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25118656)))];
tensor<fp16, [768]> blocks_1_mlp_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_1_mlp_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25120256)))];
tensor<fp16, [1, 1500, 768]> var_270_cast_fp16 = layer_norm(axes = var_270_axes_0, beta = blocks_1_mlp_ln_bias_to_fp16, epsilon = var_196_to_fp16, gamma = blocks_1_mlp_ln_weight_to_fp16, x = x_25_cast_fp16)[name = tensor<string, []>("op_270_cast_fp16")];
tensor<fp16, [3072, 768]> var_279_to_fp16 = const()[name = tensor<string, []>("op_279_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25121856)))];
tensor<fp16, [3072]> var_280_to_fp16 = const()[name = tensor<string, []>("op_280_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29840512)))];
tensor<fp16, [1, 1500, 3072]> linear_10_cast_fp16 = linear(bias = var_280_to_fp16, weight = var_279_to_fp16, x = var_270_cast_fp16)[name = tensor<string, []>("linear_10_cast_fp16")];
tensor<string, []> x_29_mode_0 = const()[name = tensor<string, []>("x_29_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 1500, 3072]> x_29_cast_fp16 = gelu(mode = x_29_mode_0, x = linear_10_cast_fp16)[name = tensor<string, []>("x_29_cast_fp16")];
tensor<fp16, [768, 3072]> var_285_to_fp16 = const()[name = tensor<string, []>("op_285_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29846720)))];
tensor<fp16, [768]> var_286_to_fp16 = const()[name = tensor<string, []>("op_286_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(34565376)))];
tensor<fp16, [1, 1500, 768]> linear_11_cast_fp16 = linear(bias = var_286_to_fp16, weight = var_285_to_fp16, x = x_29_cast_fp16)[name = tensor<string, []>("linear_11_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_31_cast_fp16 = add(x = x_25_cast_fp16, y = linear_11_cast_fp16)[name = tensor<string, []>("x_31_cast_fp16")];
tensor<int32, []> var_296 = const()[name = tensor<string, []>("op_296"), val = tensor<int32, []>(-1)];
tensor<int32, [1]> var_312_axes_0 = const()[name = tensor<string, []>("op_312_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_2_attn_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_2_attn_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(34566976)))];
tensor<fp16, [768]> blocks_2_attn_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_2_attn_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(34568576)))];
tensor<fp16, []> var_302_to_fp16 = const()[name = tensor<string, []>("op_302_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
tensor<fp16, [1, 1500, 768]> var_312_cast_fp16 = layer_norm(axes = var_312_axes_0, beta = blocks_2_attn_ln_bias_to_fp16, epsilon = var_302_to_fp16, gamma = blocks_2_attn_ln_weight_to_fp16, x = x_31_cast_fp16)[name = tensor<string, []>("op_312_cast_fp16")];
tensor<fp16, [768, 768]> var_323_to_fp16 = const()[name = tensor<string, []>("op_323_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(34570176)))];
tensor<fp16, [768]> var_324_to_fp16 = const()[name = tensor<string, []>("op_324_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35749888)))];
tensor<fp16, [1, 1500, 768]> linear_12_cast_fp16 = linear(bias = var_324_to_fp16, weight = var_323_to_fp16, x = var_312_cast_fp16)[name = tensor<string, []>("linear_12_cast_fp16")];
tensor<fp16, [768, 768]> var_327_to_fp16 = const()[name = tensor<string, []>("op_327_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35751488)))];
tensor<fp16, [1, 1500, 768]> linear_13_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = var_327_to_fp16, x = var_312_cast_fp16)[name = tensor<string, []>("linear_13_cast_fp16")];
tensor<fp16, [768, 768]> var_331_to_fp16 = const()[name = tensor<string, []>("op_331_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36931200)))];
tensor<fp16, [768]> var_332_to_fp16 = const()[name = tensor<string, []>("op_332_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38110912)))];
tensor<fp16, [1, 1500, 768]> linear_14_cast_fp16 = linear(bias = var_332_to_fp16, weight = var_331_to_fp16, x = var_312_cast_fp16)[name = tensor<string, []>("linear_14_cast_fp16")];
tensor<int32, [4]> var_340 = const()[name = tensor<string, []>("op_340"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_341_cast_fp16 = reshape(shape = var_340, x = linear_12_cast_fp16)[name = tensor<string, []>("op_341_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_88_to_fp16 = const()[name = tensor<string, []>("const_88_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> q_11_cast_fp16 = mul(x = var_341_cast_fp16, y = const_88_to_fp16)[name = tensor<string, []>("q_11_cast_fp16")];
tensor<int32, [4]> var_347 = const()[name = tensor<string, []>("op_347"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_348_cast_fp16 = reshape(shape = var_347, x = linear_13_cast_fp16)[name = tensor<string, []>("op_348_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_89_to_fp16 = const()[name = tensor<string, []>("const_89_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> k_11_cast_fp16 = mul(x = var_348_cast_fp16, y = const_89_to_fp16)[name = tensor<string, []>("k_11_cast_fp16")];
tensor<int32, [4]> var_354 = const()[name = tensor<string, []>("op_354"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_355_cast_fp16 = reshape(shape = var_354, x = linear_14_cast_fp16)[name = tensor<string, []>("op_355_cast_fp16")];
tensor<int32, [4]> var_356 = const()[name = tensor<string, []>("op_356"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<bool, []> qk_5_transpose_x_0 = const()[name = tensor<string, []>("qk_5_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> qk_5_transpose_y_0 = const()[name = tensor<string, []>("qk_5_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<int32, [4]> transpose_52_perm_0 = const()[name = tensor<string, []>("transpose_52_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
tensor<int32, [4]> transpose_53_perm_0 = const()[name = tensor<string, []>("transpose_53_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
tensor<fp16, [1, 12, 64, 1500]> transpose_109 = transpose(perm = transpose_53_perm_0, x = k_11_cast_fp16)[name = tensor<string, []>("transpose_109")];
tensor<fp16, [1, 12, 1500, 64]> transpose_110 = transpose(perm = transpose_52_perm_0, x = q_11_cast_fp16)[name = tensor<string, []>("transpose_110")];
tensor<fp16, [1, 12, 1500, 1500]> qk_5_cast_fp16 = matmul(transpose_x = qk_5_transpose_x_0, transpose_y = qk_5_transpose_y_0, x = transpose_110, y = transpose_109)[name = tensor<string, []>("qk_5_cast_fp16")];
tensor<fp16, [1, 12, 1500, 1500]> var_360_cast_fp16 = softmax(axis = var_296, x = qk_5_cast_fp16)[name = tensor<string, []>("op_360_cast_fp16")];
tensor<bool, []> var_362_transpose_x_0 = const()[name = tensor<string, []>("op_362_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> var_362_transpose_y_0 = const()[name = tensor<string, []>("op_362_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [1, 12, 1500, 64]> transpose_111 = transpose(perm = var_356, x = var_355_cast_fp16)[name = tensor<string, []>("transpose_111")];
tensor<fp16, [1, 12, 1500, 64]> var_362_cast_fp16 = matmul(transpose_x = var_362_transpose_x_0, transpose_y = var_362_transpose_y_0, x = var_360_cast_fp16, y = transpose_111)[name = tensor<string, []>("op_362_cast_fp16")];
tensor<int32, [4]> var_363 = const()[name = tensor<string, []>("op_363"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> concat_2 = const()[name = tensor<string, []>("concat_2"), val = tensor<int32, [3]>([1, 1500, 768])];
tensor<fp16, [1, 1500, 12, 64]> transpose_108 = transpose(perm = var_363, x = var_362_cast_fp16)[name = tensor<string, []>("transpose_108")];
tensor<fp16, [1, 1500, 768]> x_35_cast_fp16 = reshape(shape = concat_2, x = transpose_108)[name = tensor<string, []>("x_35_cast_fp16")];
tensor<fp16, [768, 768]> var_368_to_fp16 = const()[name = tensor<string, []>("op_368_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38112512)))];
tensor<fp16, [768]> var_369_to_fp16 = const()[name = tensor<string, []>("op_369_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39292224)))];
tensor<fp16, [1, 1500, 768]> linear_15_cast_fp16 = linear(bias = var_369_to_fp16, weight = var_368_to_fp16, x = x_35_cast_fp16)[name = tensor<string, []>("linear_15_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_37_cast_fp16 = add(x = x_31_cast_fp16, y = linear_15_cast_fp16)[name = tensor<string, []>("x_37_cast_fp16")];
tensor<int32, [1]> var_376_axes_0 = const()[name = tensor<string, []>("op_376_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_2_mlp_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_2_mlp_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39293824)))];
tensor<fp16, [768]> blocks_2_mlp_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_2_mlp_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39295424)))];
tensor<fp16, [1, 1500, 768]> var_376_cast_fp16 = layer_norm(axes = var_376_axes_0, beta = blocks_2_mlp_ln_bias_to_fp16, epsilon = var_302_to_fp16, gamma = blocks_2_mlp_ln_weight_to_fp16, x = x_37_cast_fp16)[name = tensor<string, []>("op_376_cast_fp16")];
tensor<fp16, [3072, 768]> var_385_to_fp16 = const()[name = tensor<string, []>("op_385_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39297024)))];
tensor<fp16, [3072]> var_386_to_fp16 = const()[name = tensor<string, []>("op_386_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44015680)))];
tensor<fp16, [1, 1500, 3072]> linear_16_cast_fp16 = linear(bias = var_386_to_fp16, weight = var_385_to_fp16, x = var_376_cast_fp16)[name = tensor<string, []>("linear_16_cast_fp16")];
tensor<string, []> x_41_mode_0 = const()[name = tensor<string, []>("x_41_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 1500, 3072]> x_41_cast_fp16 = gelu(mode = x_41_mode_0, x = linear_16_cast_fp16)[name = tensor<string, []>("x_41_cast_fp16")];
tensor<fp16, [768, 3072]> var_391_to_fp16 = const()[name = tensor<string, []>("op_391_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(44021888)))];
tensor<fp16, [768]> var_392_to_fp16 = const()[name = tensor<string, []>("op_392_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48740544)))];
tensor<fp16, [1, 1500, 768]> linear_17_cast_fp16 = linear(bias = var_392_to_fp16, weight = var_391_to_fp16, x = x_41_cast_fp16)[name = tensor<string, []>("linear_17_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_43_cast_fp16 = add(x = x_37_cast_fp16, y = linear_17_cast_fp16)[name = tensor<string, []>("x_43_cast_fp16")];
tensor<int32, []> var_402 = const()[name = tensor<string, []>("op_402"), val = tensor<int32, []>(-1)];
tensor<int32, [1]> var_418_axes_0 = const()[name = tensor<string, []>("op_418_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_3_attn_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_3_attn_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48742144)))];
tensor<fp16, [768]> blocks_3_attn_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_3_attn_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48743744)))];
tensor<fp16, []> var_408_to_fp16 = const()[name = tensor<string, []>("op_408_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
tensor<fp16, [1, 1500, 768]> var_418_cast_fp16 = layer_norm(axes = var_418_axes_0, beta = blocks_3_attn_ln_bias_to_fp16, epsilon = var_408_to_fp16, gamma = blocks_3_attn_ln_weight_to_fp16, x = x_43_cast_fp16)[name = tensor<string, []>("op_418_cast_fp16")];
tensor<fp16, [768, 768]> var_429_to_fp16 = const()[name = tensor<string, []>("op_429_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48745344)))];
tensor<fp16, [768]> var_430_to_fp16 = const()[name = tensor<string, []>("op_430_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(49925056)))];
tensor<fp16, [1, 1500, 768]> linear_18_cast_fp16 = linear(bias = var_430_to_fp16, weight = var_429_to_fp16, x = var_418_cast_fp16)[name = tensor<string, []>("linear_18_cast_fp16")];
tensor<fp16, [768, 768]> var_433_to_fp16 = const()[name = tensor<string, []>("op_433_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(49926656)))];
tensor<fp16, [1, 1500, 768]> linear_19_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = var_433_to_fp16, x = var_418_cast_fp16)[name = tensor<string, []>("linear_19_cast_fp16")];
tensor<fp16, [768, 768]> var_437_to_fp16 = const()[name = tensor<string, []>("op_437_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(51106368)))];
tensor<fp16, [768]> var_438_to_fp16 = const()[name = tensor<string, []>("op_438_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(52286080)))];
tensor<fp16, [1, 1500, 768]> linear_20_cast_fp16 = linear(bias = var_438_to_fp16, weight = var_437_to_fp16, x = var_418_cast_fp16)[name = tensor<string, []>("linear_20_cast_fp16")];
tensor<int32, [4]> var_446 = const()[name = tensor<string, []>("op_446"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_447_cast_fp16 = reshape(shape = var_446, x = linear_18_cast_fp16)[name = tensor<string, []>("op_447_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_90_to_fp16 = const()[name = tensor<string, []>("const_90_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> q_15_cast_fp16 = mul(x = var_447_cast_fp16, y = const_90_to_fp16)[name = tensor<string, []>("q_15_cast_fp16")];
tensor<int32, [4]> var_453 = const()[name = tensor<string, []>("op_453"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_454_cast_fp16 = reshape(shape = var_453, x = linear_19_cast_fp16)[name = tensor<string, []>("op_454_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_91_to_fp16 = const()[name = tensor<string, []>("const_91_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> k_15_cast_fp16 = mul(x = var_454_cast_fp16, y = const_91_to_fp16)[name = tensor<string, []>("k_15_cast_fp16")];
tensor<int32, [4]> var_460 = const()[name = tensor<string, []>("op_460"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_461_cast_fp16 = reshape(shape = var_460, x = linear_20_cast_fp16)[name = tensor<string, []>("op_461_cast_fp16")];
tensor<int32, [4]> var_462 = const()[name = tensor<string, []>("op_462"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<bool, []> qk_7_transpose_x_0 = const()[name = tensor<string, []>("qk_7_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> qk_7_transpose_y_0 = const()[name = tensor<string, []>("qk_7_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<int32, [4]> transpose_54_perm_0 = const()[name = tensor<string, []>("transpose_54_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
tensor<int32, [4]> transpose_55_perm_0 = const()[name = tensor<string, []>("transpose_55_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
tensor<fp16, [1, 12, 64, 1500]> transpose_105 = transpose(perm = transpose_55_perm_0, x = k_15_cast_fp16)[name = tensor<string, []>("transpose_105")];
tensor<fp16, [1, 12, 1500, 64]> transpose_106 = transpose(perm = transpose_54_perm_0, x = q_15_cast_fp16)[name = tensor<string, []>("transpose_106")];
tensor<fp16, [1, 12, 1500, 1500]> qk_7_cast_fp16 = matmul(transpose_x = qk_7_transpose_x_0, transpose_y = qk_7_transpose_y_0, x = transpose_106, y = transpose_105)[name = tensor<string, []>("qk_7_cast_fp16")];
tensor<fp16, [1, 12, 1500, 1500]> var_466_cast_fp16 = softmax(axis = var_402, x = qk_7_cast_fp16)[name = tensor<string, []>("op_466_cast_fp16")];
tensor<bool, []> var_468_transpose_x_0 = const()[name = tensor<string, []>("op_468_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> var_468_transpose_y_0 = const()[name = tensor<string, []>("op_468_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [1, 12, 1500, 64]> transpose_107 = transpose(perm = var_462, x = var_461_cast_fp16)[name = tensor<string, []>("transpose_107")];
tensor<fp16, [1, 12, 1500, 64]> var_468_cast_fp16 = matmul(transpose_x = var_468_transpose_x_0, transpose_y = var_468_transpose_y_0, x = var_466_cast_fp16, y = transpose_107)[name = tensor<string, []>("op_468_cast_fp16")];
tensor<int32, [4]> var_469 = const()[name = tensor<string, []>("op_469"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> concat_3 = const()[name = tensor<string, []>("concat_3"), val = tensor<int32, [3]>([1, 1500, 768])];
tensor<fp16, [1, 1500, 12, 64]> transpose_104 = transpose(perm = var_469, x = var_468_cast_fp16)[name = tensor<string, []>("transpose_104")];
tensor<fp16, [1, 1500, 768]> x_47_cast_fp16 = reshape(shape = concat_3, x = transpose_104)[name = tensor<string, []>("x_47_cast_fp16")];
tensor<fp16, [768, 768]> var_474_to_fp16 = const()[name = tensor<string, []>("op_474_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(52287680)))];
tensor<fp16, [768]> var_475_to_fp16 = const()[name = tensor<string, []>("op_475_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(53467392)))];
tensor<fp16, [1, 1500, 768]> linear_21_cast_fp16 = linear(bias = var_475_to_fp16, weight = var_474_to_fp16, x = x_47_cast_fp16)[name = tensor<string, []>("linear_21_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_49_cast_fp16 = add(x = x_43_cast_fp16, y = linear_21_cast_fp16)[name = tensor<string, []>("x_49_cast_fp16")];
tensor<int32, [1]> var_482_axes_0 = const()[name = tensor<string, []>("op_482_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_3_mlp_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_3_mlp_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(53468992)))];
tensor<fp16, [768]> blocks_3_mlp_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_3_mlp_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(53470592)))];
tensor<fp16, [1, 1500, 768]> var_482_cast_fp16 = layer_norm(axes = var_482_axes_0, beta = blocks_3_mlp_ln_bias_to_fp16, epsilon = var_408_to_fp16, gamma = blocks_3_mlp_ln_weight_to_fp16, x = x_49_cast_fp16)[name = tensor<string, []>("op_482_cast_fp16")];
tensor<fp16, [3072, 768]> var_491_to_fp16 = const()[name = tensor<string, []>("op_491_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(53472192)))];
tensor<fp16, [3072]> var_492_to_fp16 = const()[name = tensor<string, []>("op_492_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(58190848)))];
tensor<fp16, [1, 1500, 3072]> linear_22_cast_fp16 = linear(bias = var_492_to_fp16, weight = var_491_to_fp16, x = var_482_cast_fp16)[name = tensor<string, []>("linear_22_cast_fp16")];
tensor<string, []> x_53_mode_0 = const()[name = tensor<string, []>("x_53_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 1500, 3072]> x_53_cast_fp16 = gelu(mode = x_53_mode_0, x = linear_22_cast_fp16)[name = tensor<string, []>("x_53_cast_fp16")];
tensor<fp16, [768, 3072]> var_497_to_fp16 = const()[name = tensor<string, []>("op_497_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(58197056)))];
tensor<fp16, [768]> var_498_to_fp16 = const()[name = tensor<string, []>("op_498_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(62915712)))];
tensor<fp16, [1, 1500, 768]> linear_23_cast_fp16 = linear(bias = var_498_to_fp16, weight = var_497_to_fp16, x = x_53_cast_fp16)[name = tensor<string, []>("linear_23_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_55_cast_fp16 = add(x = x_49_cast_fp16, y = linear_23_cast_fp16)[name = tensor<string, []>("x_55_cast_fp16")];
tensor<int32, []> var_508 = const()[name = tensor<string, []>("op_508"), val = tensor<int32, []>(-1)];
tensor<int32, [1]> var_524_axes_0 = const()[name = tensor<string, []>("op_524_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_4_attn_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_4_attn_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(62917312)))];
tensor<fp16, [768]> blocks_4_attn_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_4_attn_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(62918912)))];
tensor<fp16, []> var_514_to_fp16 = const()[name = tensor<string, []>("op_514_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
tensor<fp16, [1, 1500, 768]> var_524_cast_fp16 = layer_norm(axes = var_524_axes_0, beta = blocks_4_attn_ln_bias_to_fp16, epsilon = var_514_to_fp16, gamma = blocks_4_attn_ln_weight_to_fp16, x = x_55_cast_fp16)[name = tensor<string, []>("op_524_cast_fp16")];
tensor<fp16, [768, 768]> var_535_to_fp16 = const()[name = tensor<string, []>("op_535_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(62920512)))];
tensor<fp16, [768]> var_536_to_fp16 = const()[name = tensor<string, []>("op_536_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64100224)))];
tensor<fp16, [1, 1500, 768]> linear_24_cast_fp16 = linear(bias = var_536_to_fp16, weight = var_535_to_fp16, x = var_524_cast_fp16)[name = tensor<string, []>("linear_24_cast_fp16")];
tensor<fp16, [768, 768]> var_539_to_fp16 = const()[name = tensor<string, []>("op_539_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64101824)))];
tensor<fp16, [1, 1500, 768]> linear_25_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = var_539_to_fp16, x = var_524_cast_fp16)[name = tensor<string, []>("linear_25_cast_fp16")];
tensor<fp16, [768, 768]> var_543_to_fp16 = const()[name = tensor<string, []>("op_543_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(65281536)))];
tensor<fp16, [768]> var_544_to_fp16 = const()[name = tensor<string, []>("op_544_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(66461248)))];
tensor<fp16, [1, 1500, 768]> linear_26_cast_fp16 = linear(bias = var_544_to_fp16, weight = var_543_to_fp16, x = var_524_cast_fp16)[name = tensor<string, []>("linear_26_cast_fp16")];
tensor<int32, [4]> var_552 = const()[name = tensor<string, []>("op_552"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_553_cast_fp16 = reshape(shape = var_552, x = linear_24_cast_fp16)[name = tensor<string, []>("op_553_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_92_to_fp16 = const()[name = tensor<string, []>("const_92_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> q_19_cast_fp16 = mul(x = var_553_cast_fp16, y = const_92_to_fp16)[name = tensor<string, []>("q_19_cast_fp16")];
tensor<int32, [4]> var_559 = const()[name = tensor<string, []>("op_559"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_560_cast_fp16 = reshape(shape = var_559, x = linear_25_cast_fp16)[name = tensor<string, []>("op_560_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_93_to_fp16 = const()[name = tensor<string, []>("const_93_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> k_19_cast_fp16 = mul(x = var_560_cast_fp16, y = const_93_to_fp16)[name = tensor<string, []>("k_19_cast_fp16")];
tensor<int32, [4]> var_566 = const()[name = tensor<string, []>("op_566"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_567_cast_fp16 = reshape(shape = var_566, x = linear_26_cast_fp16)[name = tensor<string, []>("op_567_cast_fp16")];
tensor<int32, [4]> var_568 = const()[name = tensor<string, []>("op_568"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<bool, []> qk_9_transpose_x_0 = const()[name = tensor<string, []>("qk_9_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> qk_9_transpose_y_0 = const()[name = tensor<string, []>("qk_9_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<int32, [4]> transpose_56_perm_0 = const()[name = tensor<string, []>("transpose_56_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
tensor<int32, [4]> transpose_57_perm_0 = const()[name = tensor<string, []>("transpose_57_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
tensor<fp16, [1, 12, 64, 1500]> transpose_101 = transpose(perm = transpose_57_perm_0, x = k_19_cast_fp16)[name = tensor<string, []>("transpose_101")];
tensor<fp16, [1, 12, 1500, 64]> transpose_102 = transpose(perm = transpose_56_perm_0, x = q_19_cast_fp16)[name = tensor<string, []>("transpose_102")];
tensor<fp16, [1, 12, 1500, 1500]> qk_9_cast_fp16 = matmul(transpose_x = qk_9_transpose_x_0, transpose_y = qk_9_transpose_y_0, x = transpose_102, y = transpose_101)[name = tensor<string, []>("qk_9_cast_fp16")];
tensor<fp16, [1, 12, 1500, 1500]> var_572_cast_fp16 = softmax(axis = var_508, x = qk_9_cast_fp16)[name = tensor<string, []>("op_572_cast_fp16")];
tensor<bool, []> var_574_transpose_x_0 = const()[name = tensor<string, []>("op_574_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> var_574_transpose_y_0 = const()[name = tensor<string, []>("op_574_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [1, 12, 1500, 64]> transpose_103 = transpose(perm = var_568, x = var_567_cast_fp16)[name = tensor<string, []>("transpose_103")];
tensor<fp16, [1, 12, 1500, 64]> var_574_cast_fp16 = matmul(transpose_x = var_574_transpose_x_0, transpose_y = var_574_transpose_y_0, x = var_572_cast_fp16, y = transpose_103)[name = tensor<string, []>("op_574_cast_fp16")];
tensor<int32, [4]> var_575 = const()[name = tensor<string, []>("op_575"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> concat_4 = const()[name = tensor<string, []>("concat_4"), val = tensor<int32, [3]>([1, 1500, 768])];
tensor<fp16, [1, 1500, 12, 64]> transpose_100 = transpose(perm = var_575, x = var_574_cast_fp16)[name = tensor<string, []>("transpose_100")];
tensor<fp16, [1, 1500, 768]> x_59_cast_fp16 = reshape(shape = concat_4, x = transpose_100)[name = tensor<string, []>("x_59_cast_fp16")];
tensor<fp16, [768, 768]> var_580_to_fp16 = const()[name = tensor<string, []>("op_580_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(66462848)))];
tensor<fp16, [768]> var_581_to_fp16 = const()[name = tensor<string, []>("op_581_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(67642560)))];
tensor<fp16, [1, 1500, 768]> linear_27_cast_fp16 = linear(bias = var_581_to_fp16, weight = var_580_to_fp16, x = x_59_cast_fp16)[name = tensor<string, []>("linear_27_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_61_cast_fp16 = add(x = x_55_cast_fp16, y = linear_27_cast_fp16)[name = tensor<string, []>("x_61_cast_fp16")];
tensor<int32, [1]> var_588_axes_0 = const()[name = tensor<string, []>("op_588_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_4_mlp_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_4_mlp_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(67644160)))];
tensor<fp16, [768]> blocks_4_mlp_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_4_mlp_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(67645760)))];
tensor<fp16, [1, 1500, 768]> var_588_cast_fp16 = layer_norm(axes = var_588_axes_0, beta = blocks_4_mlp_ln_bias_to_fp16, epsilon = var_514_to_fp16, gamma = blocks_4_mlp_ln_weight_to_fp16, x = x_61_cast_fp16)[name = tensor<string, []>("op_588_cast_fp16")];
tensor<fp16, [3072, 768]> var_597_to_fp16 = const()[name = tensor<string, []>("op_597_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(67647360)))];
tensor<fp16, [3072]> var_598_to_fp16 = const()[name = tensor<string, []>("op_598_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(72366016)))];
tensor<fp16, [1, 1500, 3072]> linear_28_cast_fp16 = linear(bias = var_598_to_fp16, weight = var_597_to_fp16, x = var_588_cast_fp16)[name = tensor<string, []>("linear_28_cast_fp16")];
tensor<string, []> x_65_mode_0 = const()[name = tensor<string, []>("x_65_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 1500, 3072]> x_65_cast_fp16 = gelu(mode = x_65_mode_0, x = linear_28_cast_fp16)[name = tensor<string, []>("x_65_cast_fp16")];
tensor<fp16, [768, 3072]> var_603_to_fp16 = const()[name = tensor<string, []>("op_603_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(72372224)))];
tensor<fp16, [768]> var_604_to_fp16 = const()[name = tensor<string, []>("op_604_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(77090880)))];
tensor<fp16, [1, 1500, 768]> linear_29_cast_fp16 = linear(bias = var_604_to_fp16, weight = var_603_to_fp16, x = x_65_cast_fp16)[name = tensor<string, []>("linear_29_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_67_cast_fp16 = add(x = x_61_cast_fp16, y = linear_29_cast_fp16)[name = tensor<string, []>("x_67_cast_fp16")];
tensor<int32, []> var_614 = const()[name = tensor<string, []>("op_614"), val = tensor<int32, []>(-1)];
tensor<int32, [1]> var_630_axes_0 = const()[name = tensor<string, []>("op_630_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_5_attn_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_5_attn_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(77092480)))];
tensor<fp16, [768]> blocks_5_attn_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_5_attn_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(77094080)))];
tensor<fp16, []> var_620_to_fp16 = const()[name = tensor<string, []>("op_620_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
tensor<fp16, [1, 1500, 768]> var_630_cast_fp16 = layer_norm(axes = var_630_axes_0, beta = blocks_5_attn_ln_bias_to_fp16, epsilon = var_620_to_fp16, gamma = blocks_5_attn_ln_weight_to_fp16, x = x_67_cast_fp16)[name = tensor<string, []>("op_630_cast_fp16")];
tensor<fp16, [768, 768]> var_641_to_fp16 = const()[name = tensor<string, []>("op_641_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(77095680)))];
tensor<fp16, [768]> var_642_to_fp16 = const()[name = tensor<string, []>("op_642_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78275392)))];
tensor<fp16, [1, 1500, 768]> linear_30_cast_fp16 = linear(bias = var_642_to_fp16, weight = var_641_to_fp16, x = var_630_cast_fp16)[name = tensor<string, []>("linear_30_cast_fp16")];
tensor<fp16, [768, 768]> var_645_to_fp16 = const()[name = tensor<string, []>("op_645_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78276992)))];
tensor<fp16, [1, 1500, 768]> linear_31_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = var_645_to_fp16, x = var_630_cast_fp16)[name = tensor<string, []>("linear_31_cast_fp16")];
tensor<fp16, [768, 768]> var_649_to_fp16 = const()[name = tensor<string, []>("op_649_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(79456704)))];
tensor<fp16, [768]> var_650_to_fp16 = const()[name = tensor<string, []>("op_650_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(80636416)))];
tensor<fp16, [1, 1500, 768]> linear_32_cast_fp16 = linear(bias = var_650_to_fp16, weight = var_649_to_fp16, x = var_630_cast_fp16)[name = tensor<string, []>("linear_32_cast_fp16")];
tensor<int32, [4]> var_658 = const()[name = tensor<string, []>("op_658"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_659_cast_fp16 = reshape(shape = var_658, x = linear_30_cast_fp16)[name = tensor<string, []>("op_659_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_94_to_fp16 = const()[name = tensor<string, []>("const_94_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> q_23_cast_fp16 = mul(x = var_659_cast_fp16, y = const_94_to_fp16)[name = tensor<string, []>("q_23_cast_fp16")];
tensor<int32, [4]> var_665 = const()[name = tensor<string, []>("op_665"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_666_cast_fp16 = reshape(shape = var_665, x = linear_31_cast_fp16)[name = tensor<string, []>("op_666_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_95_to_fp16 = const()[name = tensor<string, []>("const_95_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> k_23_cast_fp16 = mul(x = var_666_cast_fp16, y = const_95_to_fp16)[name = tensor<string, []>("k_23_cast_fp16")];
tensor<int32, [4]> var_672 = const()[name = tensor<string, []>("op_672"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_673_cast_fp16 = reshape(shape = var_672, x = linear_32_cast_fp16)[name = tensor<string, []>("op_673_cast_fp16")];
tensor<int32, [4]> var_674 = const()[name = tensor<string, []>("op_674"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<bool, []> qk_11_transpose_x_0 = const()[name = tensor<string, []>("qk_11_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> qk_11_transpose_y_0 = const()[name = tensor<string, []>("qk_11_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<int32, [4]> transpose_58_perm_0 = const()[name = tensor<string, []>("transpose_58_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
tensor<int32, [4]> transpose_59_perm_0 = const()[name = tensor<string, []>("transpose_59_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
tensor<fp16, [1, 12, 64, 1500]> transpose_97 = transpose(perm = transpose_59_perm_0, x = k_23_cast_fp16)[name = tensor<string, []>("transpose_97")];
tensor<fp16, [1, 12, 1500, 64]> transpose_98 = transpose(perm = transpose_58_perm_0, x = q_23_cast_fp16)[name = tensor<string, []>("transpose_98")];
tensor<fp16, [1, 12, 1500, 1500]> qk_11_cast_fp16 = matmul(transpose_x = qk_11_transpose_x_0, transpose_y = qk_11_transpose_y_0, x = transpose_98, y = transpose_97)[name = tensor<string, []>("qk_11_cast_fp16")];
tensor<fp16, [1, 12, 1500, 1500]> var_678_cast_fp16 = softmax(axis = var_614, x = qk_11_cast_fp16)[name = tensor<string, []>("op_678_cast_fp16")];
tensor<bool, []> var_680_transpose_x_0 = const()[name = tensor<string, []>("op_680_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> var_680_transpose_y_0 = const()[name = tensor<string, []>("op_680_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [1, 12, 1500, 64]> transpose_99 = transpose(perm = var_674, x = var_673_cast_fp16)[name = tensor<string, []>("transpose_99")];
tensor<fp16, [1, 12, 1500, 64]> var_680_cast_fp16 = matmul(transpose_x = var_680_transpose_x_0, transpose_y = var_680_transpose_y_0, x = var_678_cast_fp16, y = transpose_99)[name = tensor<string, []>("op_680_cast_fp16")];
tensor<int32, [4]> var_681 = const()[name = tensor<string, []>("op_681"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> concat_5 = const()[name = tensor<string, []>("concat_5"), val = tensor<int32, [3]>([1, 1500, 768])];
tensor<fp16, [1, 1500, 12, 64]> transpose_96 = transpose(perm = var_681, x = var_680_cast_fp16)[name = tensor<string, []>("transpose_96")];
tensor<fp16, [1, 1500, 768]> x_71_cast_fp16 = reshape(shape = concat_5, x = transpose_96)[name = tensor<string, []>("x_71_cast_fp16")];
tensor<fp16, [768, 768]> var_686_to_fp16 = const()[name = tensor<string, []>("op_686_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(80638016)))];
tensor<fp16, [768]> var_687_to_fp16 = const()[name = tensor<string, []>("op_687_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(81817728)))];
tensor<fp16, [1, 1500, 768]> linear_33_cast_fp16 = linear(bias = var_687_to_fp16, weight = var_686_to_fp16, x = x_71_cast_fp16)[name = tensor<string, []>("linear_33_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_73_cast_fp16 = add(x = x_67_cast_fp16, y = linear_33_cast_fp16)[name = tensor<string, []>("x_73_cast_fp16")];
tensor<int32, [1]> var_694_axes_0 = const()[name = tensor<string, []>("op_694_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_5_mlp_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_5_mlp_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(81819328)))];
tensor<fp16, [768]> blocks_5_mlp_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_5_mlp_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(81820928)))];
tensor<fp16, [1, 1500, 768]> var_694_cast_fp16 = layer_norm(axes = var_694_axes_0, beta = blocks_5_mlp_ln_bias_to_fp16, epsilon = var_620_to_fp16, gamma = blocks_5_mlp_ln_weight_to_fp16, x = x_73_cast_fp16)[name = tensor<string, []>("op_694_cast_fp16")];
tensor<fp16, [3072, 768]> var_703_to_fp16 = const()[name = tensor<string, []>("op_703_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(81822528)))];
tensor<fp16, [3072]> var_704_to_fp16 = const()[name = tensor<string, []>("op_704_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(86541184)))];
tensor<fp16, [1, 1500, 3072]> linear_34_cast_fp16 = linear(bias = var_704_to_fp16, weight = var_703_to_fp16, x = var_694_cast_fp16)[name = tensor<string, []>("linear_34_cast_fp16")];
tensor<string, []> x_77_mode_0 = const()[name = tensor<string, []>("x_77_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 1500, 3072]> x_77_cast_fp16 = gelu(mode = x_77_mode_0, x = linear_34_cast_fp16)[name = tensor<string, []>("x_77_cast_fp16")];
tensor<fp16, [768, 3072]> var_709_to_fp16 = const()[name = tensor<string, []>("op_709_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(86547392)))];
tensor<fp16, [768]> var_710_to_fp16 = const()[name = tensor<string, []>("op_710_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(91266048)))];
tensor<fp16, [1, 1500, 768]> linear_35_cast_fp16 = linear(bias = var_710_to_fp16, weight = var_709_to_fp16, x = x_77_cast_fp16)[name = tensor<string, []>("linear_35_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_79_cast_fp16 = add(x = x_73_cast_fp16, y = linear_35_cast_fp16)[name = tensor<string, []>("x_79_cast_fp16")];
tensor<int32, []> var_720 = const()[name = tensor<string, []>("op_720"), val = tensor<int32, []>(-1)];
tensor<int32, [1]> var_736_axes_0 = const()[name = tensor<string, []>("op_736_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_6_attn_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_6_attn_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(91267648)))];
tensor<fp16, [768]> blocks_6_attn_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_6_attn_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(91269248)))];
tensor<fp16, []> var_726_to_fp16 = const()[name = tensor<string, []>("op_726_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
tensor<fp16, [1, 1500, 768]> var_736_cast_fp16 = layer_norm(axes = var_736_axes_0, beta = blocks_6_attn_ln_bias_to_fp16, epsilon = var_726_to_fp16, gamma = blocks_6_attn_ln_weight_to_fp16, x = x_79_cast_fp16)[name = tensor<string, []>("op_736_cast_fp16")];
tensor<fp16, [768, 768]> var_747_to_fp16 = const()[name = tensor<string, []>("op_747_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(91270848)))];
tensor<fp16, [768]> var_748_to_fp16 = const()[name = tensor<string, []>("op_748_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(92450560)))];
tensor<fp16, [1, 1500, 768]> linear_36_cast_fp16 = linear(bias = var_748_to_fp16, weight = var_747_to_fp16, x = var_736_cast_fp16)[name = tensor<string, []>("linear_36_cast_fp16")];
tensor<fp16, [768, 768]> var_751_to_fp16 = const()[name = tensor<string, []>("op_751_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(92452160)))];
tensor<fp16, [1, 1500, 768]> linear_37_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = var_751_to_fp16, x = var_736_cast_fp16)[name = tensor<string, []>("linear_37_cast_fp16")];
tensor<fp16, [768, 768]> var_755_to_fp16 = const()[name = tensor<string, []>("op_755_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(93631872)))];
tensor<fp16, [768]> var_756_to_fp16 = const()[name = tensor<string, []>("op_756_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(94811584)))];
tensor<fp16, [1, 1500, 768]> linear_38_cast_fp16 = linear(bias = var_756_to_fp16, weight = var_755_to_fp16, x = var_736_cast_fp16)[name = tensor<string, []>("linear_38_cast_fp16")];
tensor<int32, [4]> var_764 = const()[name = tensor<string, []>("op_764"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_765_cast_fp16 = reshape(shape = var_764, x = linear_36_cast_fp16)[name = tensor<string, []>("op_765_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_96_to_fp16 = const()[name = tensor<string, []>("const_96_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> q_27_cast_fp16 = mul(x = var_765_cast_fp16, y = const_96_to_fp16)[name = tensor<string, []>("q_27_cast_fp16")];
tensor<int32, [4]> var_771 = const()[name = tensor<string, []>("op_771"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_772_cast_fp16 = reshape(shape = var_771, x = linear_37_cast_fp16)[name = tensor<string, []>("op_772_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_97_to_fp16 = const()[name = tensor<string, []>("const_97_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> k_27_cast_fp16 = mul(x = var_772_cast_fp16, y = const_97_to_fp16)[name = tensor<string, []>("k_27_cast_fp16")];
tensor<int32, [4]> var_778 = const()[name = tensor<string, []>("op_778"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_779_cast_fp16 = reshape(shape = var_778, x = linear_38_cast_fp16)[name = tensor<string, []>("op_779_cast_fp16")];
tensor<int32, [4]> var_780 = const()[name = tensor<string, []>("op_780"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<bool, []> qk_13_transpose_x_0 = const()[name = tensor<string, []>("qk_13_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> qk_13_transpose_y_0 = const()[name = tensor<string, []>("qk_13_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<int32, [4]> transpose_60_perm_0 = const()[name = tensor<string, []>("transpose_60_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
tensor<int32, [4]> transpose_61_perm_0 = const()[name = tensor<string, []>("transpose_61_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
tensor<fp16, [1, 12, 64, 1500]> transpose_93 = transpose(perm = transpose_61_perm_0, x = k_27_cast_fp16)[name = tensor<string, []>("transpose_93")];
tensor<fp16, [1, 12, 1500, 64]> transpose_94 = transpose(perm = transpose_60_perm_0, x = q_27_cast_fp16)[name = tensor<string, []>("transpose_94")];
tensor<fp16, [1, 12, 1500, 1500]> qk_13_cast_fp16 = matmul(transpose_x = qk_13_transpose_x_0, transpose_y = qk_13_transpose_y_0, x = transpose_94, y = transpose_93)[name = tensor<string, []>("qk_13_cast_fp16")];
tensor<fp16, [1, 12, 1500, 1500]> var_784_cast_fp16 = softmax(axis = var_720, x = qk_13_cast_fp16)[name = tensor<string, []>("op_784_cast_fp16")];
tensor<bool, []> var_786_transpose_x_0 = const()[name = tensor<string, []>("op_786_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> var_786_transpose_y_0 = const()[name = tensor<string, []>("op_786_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [1, 12, 1500, 64]> transpose_95 = transpose(perm = var_780, x = var_779_cast_fp16)[name = tensor<string, []>("transpose_95")];
tensor<fp16, [1, 12, 1500, 64]> var_786_cast_fp16 = matmul(transpose_x = var_786_transpose_x_0, transpose_y = var_786_transpose_y_0, x = var_784_cast_fp16, y = transpose_95)[name = tensor<string, []>("op_786_cast_fp16")];
tensor<int32, [4]> var_787 = const()[name = tensor<string, []>("op_787"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> concat_6 = const()[name = tensor<string, []>("concat_6"), val = tensor<int32, [3]>([1, 1500, 768])];
tensor<fp16, [1, 1500, 12, 64]> transpose_92 = transpose(perm = var_787, x = var_786_cast_fp16)[name = tensor<string, []>("transpose_92")];
tensor<fp16, [1, 1500, 768]> x_83_cast_fp16 = reshape(shape = concat_6, x = transpose_92)[name = tensor<string, []>("x_83_cast_fp16")];
tensor<fp16, [768, 768]> var_792_to_fp16 = const()[name = tensor<string, []>("op_792_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(94813184)))];
tensor<fp16, [768]> var_793_to_fp16 = const()[name = tensor<string, []>("op_793_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95992896)))];
tensor<fp16, [1, 1500, 768]> linear_39_cast_fp16 = linear(bias = var_793_to_fp16, weight = var_792_to_fp16, x = x_83_cast_fp16)[name = tensor<string, []>("linear_39_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_85_cast_fp16 = add(x = x_79_cast_fp16, y = linear_39_cast_fp16)[name = tensor<string, []>("x_85_cast_fp16")];
tensor<int32, [1]> var_800_axes_0 = const()[name = tensor<string, []>("op_800_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_6_mlp_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_6_mlp_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95994496)))];
tensor<fp16, [768]> blocks_6_mlp_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_6_mlp_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95996096)))];
tensor<fp16, [1, 1500, 768]> var_800_cast_fp16 = layer_norm(axes = var_800_axes_0, beta = blocks_6_mlp_ln_bias_to_fp16, epsilon = var_726_to_fp16, gamma = blocks_6_mlp_ln_weight_to_fp16, x = x_85_cast_fp16)[name = tensor<string, []>("op_800_cast_fp16")];
tensor<fp16, [3072, 768]> var_809_to_fp16 = const()[name = tensor<string, []>("op_809_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95997696)))];
tensor<fp16, [3072]> var_810_to_fp16 = const()[name = tensor<string, []>("op_810_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(100716352)))];
tensor<fp16, [1, 1500, 3072]> linear_40_cast_fp16 = linear(bias = var_810_to_fp16, weight = var_809_to_fp16, x = var_800_cast_fp16)[name = tensor<string, []>("linear_40_cast_fp16")];
tensor<string, []> x_89_mode_0 = const()[name = tensor<string, []>("x_89_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 1500, 3072]> x_89_cast_fp16 = gelu(mode = x_89_mode_0, x = linear_40_cast_fp16)[name = tensor<string, []>("x_89_cast_fp16")];
tensor<fp16, [768, 3072]> var_815_to_fp16 = const()[name = tensor<string, []>("op_815_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(100722560)))];
tensor<fp16, [768]> var_816_to_fp16 = const()[name = tensor<string, []>("op_816_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(105441216)))];
tensor<fp16, [1, 1500, 768]> linear_41_cast_fp16 = linear(bias = var_816_to_fp16, weight = var_815_to_fp16, x = x_89_cast_fp16)[name = tensor<string, []>("linear_41_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_91_cast_fp16 = add(x = x_85_cast_fp16, y = linear_41_cast_fp16)[name = tensor<string, []>("x_91_cast_fp16")];
tensor<int32, []> var_826 = const()[name = tensor<string, []>("op_826"), val = tensor<int32, []>(-1)];
tensor<int32, [1]> var_842_axes_0 = const()[name = tensor<string, []>("op_842_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_7_attn_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_7_attn_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(105442816)))];
tensor<fp16, [768]> blocks_7_attn_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_7_attn_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(105444416)))];
tensor<fp16, []> var_832_to_fp16 = const()[name = tensor<string, []>("op_832_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
tensor<fp16, [1, 1500, 768]> var_842_cast_fp16 = layer_norm(axes = var_842_axes_0, beta = blocks_7_attn_ln_bias_to_fp16, epsilon = var_832_to_fp16, gamma = blocks_7_attn_ln_weight_to_fp16, x = x_91_cast_fp16)[name = tensor<string, []>("op_842_cast_fp16")];
tensor<fp16, [768, 768]> var_853_to_fp16 = const()[name = tensor<string, []>("op_853_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(105446016)))];
tensor<fp16, [768]> var_854_to_fp16 = const()[name = tensor<string, []>("op_854_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(106625728)))];
tensor<fp16, [1, 1500, 768]> linear_42_cast_fp16 = linear(bias = var_854_to_fp16, weight = var_853_to_fp16, x = var_842_cast_fp16)[name = tensor<string, []>("linear_42_cast_fp16")];
tensor<fp16, [768, 768]> var_857_to_fp16 = const()[name = tensor<string, []>("op_857_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(106627328)))];
tensor<fp16, [1, 1500, 768]> linear_43_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = var_857_to_fp16, x = var_842_cast_fp16)[name = tensor<string, []>("linear_43_cast_fp16")];
tensor<fp16, [768, 768]> var_861_to_fp16 = const()[name = tensor<string, []>("op_861_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(107807040)))];
tensor<fp16, [768]> var_862_to_fp16 = const()[name = tensor<string, []>("op_862_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(108986752)))];
tensor<fp16, [1, 1500, 768]> linear_44_cast_fp16 = linear(bias = var_862_to_fp16, weight = var_861_to_fp16, x = var_842_cast_fp16)[name = tensor<string, []>("linear_44_cast_fp16")];
tensor<int32, [4]> var_870 = const()[name = tensor<string, []>("op_870"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_871_cast_fp16 = reshape(shape = var_870, x = linear_42_cast_fp16)[name = tensor<string, []>("op_871_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_98_to_fp16 = const()[name = tensor<string, []>("const_98_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> q_31_cast_fp16 = mul(x = var_871_cast_fp16, y = const_98_to_fp16)[name = tensor<string, []>("q_31_cast_fp16")];
tensor<int32, [4]> var_877 = const()[name = tensor<string, []>("op_877"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_878_cast_fp16 = reshape(shape = var_877, x = linear_43_cast_fp16)[name = tensor<string, []>("op_878_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_99_to_fp16 = const()[name = tensor<string, []>("const_99_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> k_31_cast_fp16 = mul(x = var_878_cast_fp16, y = const_99_to_fp16)[name = tensor<string, []>("k_31_cast_fp16")];
tensor<int32, [4]> var_884 = const()[name = tensor<string, []>("op_884"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_885_cast_fp16 = reshape(shape = var_884, x = linear_44_cast_fp16)[name = tensor<string, []>("op_885_cast_fp16")];
tensor<int32, [4]> var_886 = const()[name = tensor<string, []>("op_886"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<bool, []> qk_15_transpose_x_0 = const()[name = tensor<string, []>("qk_15_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> qk_15_transpose_y_0 = const()[name = tensor<string, []>("qk_15_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<int32, [4]> transpose_62_perm_0 = const()[name = tensor<string, []>("transpose_62_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
tensor<int32, [4]> transpose_63_perm_0 = const()[name = tensor<string, []>("transpose_63_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
tensor<fp16, [1, 12, 64, 1500]> transpose_89 = transpose(perm = transpose_63_perm_0, x = k_31_cast_fp16)[name = tensor<string, []>("transpose_89")];
tensor<fp16, [1, 12, 1500, 64]> transpose_90 = transpose(perm = transpose_62_perm_0, x = q_31_cast_fp16)[name = tensor<string, []>("transpose_90")];
tensor<fp16, [1, 12, 1500, 1500]> qk_15_cast_fp16 = matmul(transpose_x = qk_15_transpose_x_0, transpose_y = qk_15_transpose_y_0, x = transpose_90, y = transpose_89)[name = tensor<string, []>("qk_15_cast_fp16")];
tensor<fp16, [1, 12, 1500, 1500]> var_890_cast_fp16 = softmax(axis = var_826, x = qk_15_cast_fp16)[name = tensor<string, []>("op_890_cast_fp16")];
tensor<bool, []> var_892_transpose_x_0 = const()[name = tensor<string, []>("op_892_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> var_892_transpose_y_0 = const()[name = tensor<string, []>("op_892_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [1, 12, 1500, 64]> transpose_91 = transpose(perm = var_886, x = var_885_cast_fp16)[name = tensor<string, []>("transpose_91")];
tensor<fp16, [1, 12, 1500, 64]> var_892_cast_fp16 = matmul(transpose_x = var_892_transpose_x_0, transpose_y = var_892_transpose_y_0, x = var_890_cast_fp16, y = transpose_91)[name = tensor<string, []>("op_892_cast_fp16")];
tensor<int32, [4]> var_893 = const()[name = tensor<string, []>("op_893"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> concat_7 = const()[name = tensor<string, []>("concat_7"), val = tensor<int32, [3]>([1, 1500, 768])];
tensor<fp16, [1, 1500, 12, 64]> transpose_88 = transpose(perm = var_893, x = var_892_cast_fp16)[name = tensor<string, []>("transpose_88")];
tensor<fp16, [1, 1500, 768]> x_95_cast_fp16 = reshape(shape = concat_7, x = transpose_88)[name = tensor<string, []>("x_95_cast_fp16")];
tensor<fp16, [768, 768]> var_898_to_fp16 = const()[name = tensor<string, []>("op_898_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(108988352)))];
tensor<fp16, [768]> var_899_to_fp16 = const()[name = tensor<string, []>("op_899_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(110168064)))];
tensor<fp16, [1, 1500, 768]> linear_45_cast_fp16 = linear(bias = var_899_to_fp16, weight = var_898_to_fp16, x = x_95_cast_fp16)[name = tensor<string, []>("linear_45_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_97_cast_fp16 = add(x = x_91_cast_fp16, y = linear_45_cast_fp16)[name = tensor<string, []>("x_97_cast_fp16")];
tensor<int32, [1]> var_906_axes_0 = const()[name = tensor<string, []>("op_906_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_7_mlp_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_7_mlp_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(110169664)))];
tensor<fp16, [768]> blocks_7_mlp_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_7_mlp_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(110171264)))];
tensor<fp16, [1, 1500, 768]> var_906_cast_fp16 = layer_norm(axes = var_906_axes_0, beta = blocks_7_mlp_ln_bias_to_fp16, epsilon = var_832_to_fp16, gamma = blocks_7_mlp_ln_weight_to_fp16, x = x_97_cast_fp16)[name = tensor<string, []>("op_906_cast_fp16")];
tensor<fp16, [3072, 768]> var_915_to_fp16 = const()[name = tensor<string, []>("op_915_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(110172864)))];
tensor<fp16, [3072]> var_916_to_fp16 = const()[name = tensor<string, []>("op_916_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(114891520)))];
tensor<fp16, [1, 1500, 3072]> linear_46_cast_fp16 = linear(bias = var_916_to_fp16, weight = var_915_to_fp16, x = var_906_cast_fp16)[name = tensor<string, []>("linear_46_cast_fp16")];
tensor<string, []> x_101_mode_0 = const()[name = tensor<string, []>("x_101_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 1500, 3072]> x_101_cast_fp16 = gelu(mode = x_101_mode_0, x = linear_46_cast_fp16)[name = tensor<string, []>("x_101_cast_fp16")];
tensor<fp16, [768, 3072]> var_921_to_fp16 = const()[name = tensor<string, []>("op_921_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(114897728)))];
tensor<fp16, [768]> var_922_to_fp16 = const()[name = tensor<string, []>("op_922_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(119616384)))];
tensor<fp16, [1, 1500, 768]> linear_47_cast_fp16 = linear(bias = var_922_to_fp16, weight = var_921_to_fp16, x = x_101_cast_fp16)[name = tensor<string, []>("linear_47_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_103_cast_fp16 = add(x = x_97_cast_fp16, y = linear_47_cast_fp16)[name = tensor<string, []>("x_103_cast_fp16")];
tensor<int32, []> var_932 = const()[name = tensor<string, []>("op_932"), val = tensor<int32, []>(-1)];
tensor<int32, [1]> var_948_axes_0 = const()[name = tensor<string, []>("op_948_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_8_attn_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_8_attn_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(119617984)))];
tensor<fp16, [768]> blocks_8_attn_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_8_attn_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(119619584)))];
tensor<fp16, []> var_938_to_fp16 = const()[name = tensor<string, []>("op_938_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
tensor<fp16, [1, 1500, 768]> var_948_cast_fp16 = layer_norm(axes = var_948_axes_0, beta = blocks_8_attn_ln_bias_to_fp16, epsilon = var_938_to_fp16, gamma = blocks_8_attn_ln_weight_to_fp16, x = x_103_cast_fp16)[name = tensor<string, []>("op_948_cast_fp16")];
tensor<fp16, [768, 768]> var_959_to_fp16 = const()[name = tensor<string, []>("op_959_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(119621184)))];
tensor<fp16, [768]> var_960_to_fp16 = const()[name = tensor<string, []>("op_960_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(120800896)))];
tensor<fp16, [1, 1500, 768]> linear_48_cast_fp16 = linear(bias = var_960_to_fp16, weight = var_959_to_fp16, x = var_948_cast_fp16)[name = tensor<string, []>("linear_48_cast_fp16")];
tensor<fp16, [768, 768]> var_963_to_fp16 = const()[name = tensor<string, []>("op_963_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(120802496)))];
tensor<fp16, [1, 1500, 768]> linear_49_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = var_963_to_fp16, x = var_948_cast_fp16)[name = tensor<string, []>("linear_49_cast_fp16")];
tensor<fp16, [768, 768]> var_967_to_fp16 = const()[name = tensor<string, []>("op_967_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(121982208)))];
tensor<fp16, [768]> var_968_to_fp16 = const()[name = tensor<string, []>("op_968_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(123161920)))];
tensor<fp16, [1, 1500, 768]> linear_50_cast_fp16 = linear(bias = var_968_to_fp16, weight = var_967_to_fp16, x = var_948_cast_fp16)[name = tensor<string, []>("linear_50_cast_fp16")];
tensor<int32, [4]> var_976 = const()[name = tensor<string, []>("op_976"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_977_cast_fp16 = reshape(shape = var_976, x = linear_48_cast_fp16)[name = tensor<string, []>("op_977_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_100_to_fp16 = const()[name = tensor<string, []>("const_100_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> q_35_cast_fp16 = mul(x = var_977_cast_fp16, y = const_100_to_fp16)[name = tensor<string, []>("q_35_cast_fp16")];
tensor<int32, [4]> var_983 = const()[name = tensor<string, []>("op_983"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_984_cast_fp16 = reshape(shape = var_983, x = linear_49_cast_fp16)[name = tensor<string, []>("op_984_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_101_to_fp16 = const()[name = tensor<string, []>("const_101_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> k_35_cast_fp16 = mul(x = var_984_cast_fp16, y = const_101_to_fp16)[name = tensor<string, []>("k_35_cast_fp16")];
tensor<int32, [4]> var_990 = const()[name = tensor<string, []>("op_990"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_991_cast_fp16 = reshape(shape = var_990, x = linear_50_cast_fp16)[name = tensor<string, []>("op_991_cast_fp16")];
tensor<int32, [4]> var_992 = const()[name = tensor<string, []>("op_992"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<bool, []> qk_17_transpose_x_0 = const()[name = tensor<string, []>("qk_17_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> qk_17_transpose_y_0 = const()[name = tensor<string, []>("qk_17_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<int32, [4]> transpose_64_perm_0 = const()[name = tensor<string, []>("transpose_64_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
tensor<int32, [4]> transpose_65_perm_0 = const()[name = tensor<string, []>("transpose_65_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
tensor<fp16, [1, 12, 64, 1500]> transpose_85 = transpose(perm = transpose_65_perm_0, x = k_35_cast_fp16)[name = tensor<string, []>("transpose_85")];
tensor<fp16, [1, 12, 1500, 64]> transpose_86 = transpose(perm = transpose_64_perm_0, x = q_35_cast_fp16)[name = tensor<string, []>("transpose_86")];
tensor<fp16, [1, 12, 1500, 1500]> qk_17_cast_fp16 = matmul(transpose_x = qk_17_transpose_x_0, transpose_y = qk_17_transpose_y_0, x = transpose_86, y = transpose_85)[name = tensor<string, []>("qk_17_cast_fp16")];
tensor<fp16, [1, 12, 1500, 1500]> var_996_cast_fp16 = softmax(axis = var_932, x = qk_17_cast_fp16)[name = tensor<string, []>("op_996_cast_fp16")];
tensor<bool, []> var_998_transpose_x_0 = const()[name = tensor<string, []>("op_998_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> var_998_transpose_y_0 = const()[name = tensor<string, []>("op_998_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [1, 12, 1500, 64]> transpose_87 = transpose(perm = var_992, x = var_991_cast_fp16)[name = tensor<string, []>("transpose_87")];
tensor<fp16, [1, 12, 1500, 64]> var_998_cast_fp16 = matmul(transpose_x = var_998_transpose_x_0, transpose_y = var_998_transpose_y_0, x = var_996_cast_fp16, y = transpose_87)[name = tensor<string, []>("op_998_cast_fp16")];
tensor<int32, [4]> var_999 = const()[name = tensor<string, []>("op_999"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> concat_8 = const()[name = tensor<string, []>("concat_8"), val = tensor<int32, [3]>([1, 1500, 768])];
tensor<fp16, [1, 1500, 12, 64]> transpose_84 = transpose(perm = var_999, x = var_998_cast_fp16)[name = tensor<string, []>("transpose_84")];
tensor<fp16, [1, 1500, 768]> x_107_cast_fp16 = reshape(shape = concat_8, x = transpose_84)[name = tensor<string, []>("x_107_cast_fp16")];
tensor<fp16, [768, 768]> var_1004_to_fp16 = const()[name = tensor<string, []>("op_1004_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(123163520)))];
tensor<fp16, [768]> var_1005_to_fp16 = const()[name = tensor<string, []>("op_1005_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(124343232)))];
tensor<fp16, [1, 1500, 768]> linear_51_cast_fp16 = linear(bias = var_1005_to_fp16, weight = var_1004_to_fp16, x = x_107_cast_fp16)[name = tensor<string, []>("linear_51_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_109_cast_fp16 = add(x = x_103_cast_fp16, y = linear_51_cast_fp16)[name = tensor<string, []>("x_109_cast_fp16")];
tensor<int32, [1]> var_1012_axes_0 = const()[name = tensor<string, []>("op_1012_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_8_mlp_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_8_mlp_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(124344832)))];
tensor<fp16, [768]> blocks_8_mlp_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_8_mlp_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(124346432)))];
tensor<fp16, [1, 1500, 768]> var_1012_cast_fp16 = layer_norm(axes = var_1012_axes_0, beta = blocks_8_mlp_ln_bias_to_fp16, epsilon = var_938_to_fp16, gamma = blocks_8_mlp_ln_weight_to_fp16, x = x_109_cast_fp16)[name = tensor<string, []>("op_1012_cast_fp16")];
tensor<fp16, [3072, 768]> var_1021_to_fp16 = const()[name = tensor<string, []>("op_1021_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(124348032)))];
tensor<fp16, [3072]> var_1022_to_fp16 = const()[name = tensor<string, []>("op_1022_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(129066688)))];
tensor<fp16, [1, 1500, 3072]> linear_52_cast_fp16 = linear(bias = var_1022_to_fp16, weight = var_1021_to_fp16, x = var_1012_cast_fp16)[name = tensor<string, []>("linear_52_cast_fp16")];
tensor<string, []> x_113_mode_0 = const()[name = tensor<string, []>("x_113_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 1500, 3072]> x_113_cast_fp16 = gelu(mode = x_113_mode_0, x = linear_52_cast_fp16)[name = tensor<string, []>("x_113_cast_fp16")];
tensor<fp16, [768, 3072]> var_1027_to_fp16 = const()[name = tensor<string, []>("op_1027_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(129072896)))];
tensor<fp16, [768]> var_1028_to_fp16 = const()[name = tensor<string, []>("op_1028_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133791552)))];
tensor<fp16, [1, 1500, 768]> linear_53_cast_fp16 = linear(bias = var_1028_to_fp16, weight = var_1027_to_fp16, x = x_113_cast_fp16)[name = tensor<string, []>("linear_53_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_115_cast_fp16 = add(x = x_109_cast_fp16, y = linear_53_cast_fp16)[name = tensor<string, []>("x_115_cast_fp16")];
tensor<int32, []> var_1038 = const()[name = tensor<string, []>("op_1038"), val = tensor<int32, []>(-1)];
tensor<int32, [1]> var_1054_axes_0 = const()[name = tensor<string, []>("op_1054_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_9_attn_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_9_attn_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133793152)))];
tensor<fp16, [768]> blocks_9_attn_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_9_attn_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133794752)))];
tensor<fp16, []> var_1044_to_fp16 = const()[name = tensor<string, []>("op_1044_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
tensor<fp16, [1, 1500, 768]> var_1054_cast_fp16 = layer_norm(axes = var_1054_axes_0, beta = blocks_9_attn_ln_bias_to_fp16, epsilon = var_1044_to_fp16, gamma = blocks_9_attn_ln_weight_to_fp16, x = x_115_cast_fp16)[name = tensor<string, []>("op_1054_cast_fp16")];
tensor<fp16, [768, 768]> var_1065_to_fp16 = const()[name = tensor<string, []>("op_1065_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133796352)))];
tensor<fp16, [768]> var_1066_to_fp16 = const()[name = tensor<string, []>("op_1066_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(134976064)))];
tensor<fp16, [1, 1500, 768]> linear_54_cast_fp16 = linear(bias = var_1066_to_fp16, weight = var_1065_to_fp16, x = var_1054_cast_fp16)[name = tensor<string, []>("linear_54_cast_fp16")];
tensor<fp16, [768, 768]> var_1069_to_fp16 = const()[name = tensor<string, []>("op_1069_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(134977664)))];
tensor<fp16, [1, 1500, 768]> linear_55_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = var_1069_to_fp16, x = var_1054_cast_fp16)[name = tensor<string, []>("linear_55_cast_fp16")];
tensor<fp16, [768, 768]> var_1073_to_fp16 = const()[name = tensor<string, []>("op_1073_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136157376)))];
tensor<fp16, [768]> var_1074_to_fp16 = const()[name = tensor<string, []>("op_1074_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(137337088)))];
tensor<fp16, [1, 1500, 768]> linear_56_cast_fp16 = linear(bias = var_1074_to_fp16, weight = var_1073_to_fp16, x = var_1054_cast_fp16)[name = tensor<string, []>("linear_56_cast_fp16")];
tensor<int32, [4]> var_1082 = const()[name = tensor<string, []>("op_1082"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_1083_cast_fp16 = reshape(shape = var_1082, x = linear_54_cast_fp16)[name = tensor<string, []>("op_1083_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_102_to_fp16 = const()[name = tensor<string, []>("const_102_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> q_39_cast_fp16 = mul(x = var_1083_cast_fp16, y = const_102_to_fp16)[name = tensor<string, []>("q_39_cast_fp16")];
tensor<int32, [4]> var_1089 = const()[name = tensor<string, []>("op_1089"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_1090_cast_fp16 = reshape(shape = var_1089, x = linear_55_cast_fp16)[name = tensor<string, []>("op_1090_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_103_to_fp16 = const()[name = tensor<string, []>("const_103_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> k_39_cast_fp16 = mul(x = var_1090_cast_fp16, y = const_103_to_fp16)[name = tensor<string, []>("k_39_cast_fp16")];
tensor<int32, [4]> var_1096 = const()[name = tensor<string, []>("op_1096"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_1097_cast_fp16 = reshape(shape = var_1096, x = linear_56_cast_fp16)[name = tensor<string, []>("op_1097_cast_fp16")];
tensor<int32, [4]> var_1098 = const()[name = tensor<string, []>("op_1098"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<bool, []> qk_19_transpose_x_0 = const()[name = tensor<string, []>("qk_19_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> qk_19_transpose_y_0 = const()[name = tensor<string, []>("qk_19_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<int32, [4]> transpose_66_perm_0 = const()[name = tensor<string, []>("transpose_66_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
tensor<int32, [4]> transpose_67_perm_0 = const()[name = tensor<string, []>("transpose_67_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
tensor<fp16, [1, 12, 64, 1500]> transpose_81 = transpose(perm = transpose_67_perm_0, x = k_39_cast_fp16)[name = tensor<string, []>("transpose_81")];
tensor<fp16, [1, 12, 1500, 64]> transpose_82 = transpose(perm = transpose_66_perm_0, x = q_39_cast_fp16)[name = tensor<string, []>("transpose_82")];
tensor<fp16, [1, 12, 1500, 1500]> qk_19_cast_fp16 = matmul(transpose_x = qk_19_transpose_x_0, transpose_y = qk_19_transpose_y_0, x = transpose_82, y = transpose_81)[name = tensor<string, []>("qk_19_cast_fp16")];
tensor<fp16, [1, 12, 1500, 1500]> var_1102_cast_fp16 = softmax(axis = var_1038, x = qk_19_cast_fp16)[name = tensor<string, []>("op_1102_cast_fp16")];
tensor<bool, []> var_1104_transpose_x_0 = const()[name = tensor<string, []>("op_1104_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> var_1104_transpose_y_0 = const()[name = tensor<string, []>("op_1104_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [1, 12, 1500, 64]> transpose_83 = transpose(perm = var_1098, x = var_1097_cast_fp16)[name = tensor<string, []>("transpose_83")];
tensor<fp16, [1, 12, 1500, 64]> var_1104_cast_fp16 = matmul(transpose_x = var_1104_transpose_x_0, transpose_y = var_1104_transpose_y_0, x = var_1102_cast_fp16, y = transpose_83)[name = tensor<string, []>("op_1104_cast_fp16")];
tensor<int32, [4]> var_1105 = const()[name = tensor<string, []>("op_1105"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> concat_9 = const()[name = tensor<string, []>("concat_9"), val = tensor<int32, [3]>([1, 1500, 768])];
tensor<fp16, [1, 1500, 12, 64]> transpose_80 = transpose(perm = var_1105, x = var_1104_cast_fp16)[name = tensor<string, []>("transpose_80")];
tensor<fp16, [1, 1500, 768]> x_119_cast_fp16 = reshape(shape = concat_9, x = transpose_80)[name = tensor<string, []>("x_119_cast_fp16")];
tensor<fp16, [768, 768]> var_1110_to_fp16 = const()[name = tensor<string, []>("op_1110_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(137338688)))];
tensor<fp16, [768]> var_1111_to_fp16 = const()[name = tensor<string, []>("op_1111_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(138518400)))];
tensor<fp16, [1, 1500, 768]> linear_57_cast_fp16 = linear(bias = var_1111_to_fp16, weight = var_1110_to_fp16, x = x_119_cast_fp16)[name = tensor<string, []>("linear_57_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_121_cast_fp16 = add(x = x_115_cast_fp16, y = linear_57_cast_fp16)[name = tensor<string, []>("x_121_cast_fp16")];
tensor<int32, [1]> var_1118_axes_0 = const()[name = tensor<string, []>("op_1118_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_9_mlp_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_9_mlp_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(138520000)))];
tensor<fp16, [768]> blocks_9_mlp_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_9_mlp_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(138521600)))];
tensor<fp16, [1, 1500, 768]> var_1118_cast_fp16 = layer_norm(axes = var_1118_axes_0, beta = blocks_9_mlp_ln_bias_to_fp16, epsilon = var_1044_to_fp16, gamma = blocks_9_mlp_ln_weight_to_fp16, x = x_121_cast_fp16)[name = tensor<string, []>("op_1118_cast_fp16")];
tensor<fp16, [3072, 768]> var_1127_to_fp16 = const()[name = tensor<string, []>("op_1127_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(138523200)))];
tensor<fp16, [3072]> var_1128_to_fp16 = const()[name = tensor<string, []>("op_1128_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(143241856)))];
tensor<fp16, [1, 1500, 3072]> linear_58_cast_fp16 = linear(bias = var_1128_to_fp16, weight = var_1127_to_fp16, x = var_1118_cast_fp16)[name = tensor<string, []>("linear_58_cast_fp16")];
tensor<string, []> x_125_mode_0 = const()[name = tensor<string, []>("x_125_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 1500, 3072]> x_125_cast_fp16 = gelu(mode = x_125_mode_0, x = linear_58_cast_fp16)[name = tensor<string, []>("x_125_cast_fp16")];
tensor<fp16, [768, 3072]> var_1133_to_fp16 = const()[name = tensor<string, []>("op_1133_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(143248064)))];
tensor<fp16, [768]> var_1134_to_fp16 = const()[name = tensor<string, []>("op_1134_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(147966720)))];
tensor<fp16, [1, 1500, 768]> linear_59_cast_fp16 = linear(bias = var_1134_to_fp16, weight = var_1133_to_fp16, x = x_125_cast_fp16)[name = tensor<string, []>("linear_59_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_127_cast_fp16 = add(x = x_121_cast_fp16, y = linear_59_cast_fp16)[name = tensor<string, []>("x_127_cast_fp16")];
tensor<int32, []> var_1144 = const()[name = tensor<string, []>("op_1144"), val = tensor<int32, []>(-1)];
tensor<int32, [1]> var_1160_axes_0 = const()[name = tensor<string, []>("op_1160_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_10_attn_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_10_attn_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(147968320)))];
tensor<fp16, [768]> blocks_10_attn_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_10_attn_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(147969920)))];
tensor<fp16, []> var_1150_to_fp16 = const()[name = tensor<string, []>("op_1150_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
tensor<fp16, [1, 1500, 768]> var_1160_cast_fp16 = layer_norm(axes = var_1160_axes_0, beta = blocks_10_attn_ln_bias_to_fp16, epsilon = var_1150_to_fp16, gamma = blocks_10_attn_ln_weight_to_fp16, x = x_127_cast_fp16)[name = tensor<string, []>("op_1160_cast_fp16")];
tensor<fp16, [768, 768]> var_1171_to_fp16 = const()[name = tensor<string, []>("op_1171_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(147971520)))];
tensor<fp16, [768]> var_1172_to_fp16 = const()[name = tensor<string, []>("op_1172_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(149151232)))];
tensor<fp16, [1, 1500, 768]> linear_60_cast_fp16 = linear(bias = var_1172_to_fp16, weight = var_1171_to_fp16, x = var_1160_cast_fp16)[name = tensor<string, []>("linear_60_cast_fp16")];
tensor<fp16, [768, 768]> var_1175_to_fp16 = const()[name = tensor<string, []>("op_1175_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(149152832)))];
tensor<fp16, [1, 1500, 768]> linear_61_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = var_1175_to_fp16, x = var_1160_cast_fp16)[name = tensor<string, []>("linear_61_cast_fp16")];
tensor<fp16, [768, 768]> var_1179_to_fp16 = const()[name = tensor<string, []>("op_1179_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(150332544)))];
tensor<fp16, [768]> var_1180_to_fp16 = const()[name = tensor<string, []>("op_1180_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(151512256)))];
tensor<fp16, [1, 1500, 768]> linear_62_cast_fp16 = linear(bias = var_1180_to_fp16, weight = var_1179_to_fp16, x = var_1160_cast_fp16)[name = tensor<string, []>("linear_62_cast_fp16")];
tensor<int32, [4]> var_1188 = const()[name = tensor<string, []>("op_1188"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_1189_cast_fp16 = reshape(shape = var_1188, x = linear_60_cast_fp16)[name = tensor<string, []>("op_1189_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_104_to_fp16 = const()[name = tensor<string, []>("const_104_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> q_43_cast_fp16 = mul(x = var_1189_cast_fp16, y = const_104_to_fp16)[name = tensor<string, []>("q_43_cast_fp16")];
tensor<int32, [4]> var_1195 = const()[name = tensor<string, []>("op_1195"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_1196_cast_fp16 = reshape(shape = var_1195, x = linear_61_cast_fp16)[name = tensor<string, []>("op_1196_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_105_to_fp16 = const()[name = tensor<string, []>("const_105_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> k_43_cast_fp16 = mul(x = var_1196_cast_fp16, y = const_105_to_fp16)[name = tensor<string, []>("k_43_cast_fp16")];
tensor<int32, [4]> var_1202 = const()[name = tensor<string, []>("op_1202"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_1203_cast_fp16 = reshape(shape = var_1202, x = linear_62_cast_fp16)[name = tensor<string, []>("op_1203_cast_fp16")];
tensor<int32, [4]> var_1204 = const()[name = tensor<string, []>("op_1204"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<bool, []> qk_21_transpose_x_0 = const()[name = tensor<string, []>("qk_21_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> qk_21_transpose_y_0 = const()[name = tensor<string, []>("qk_21_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<int32, [4]> transpose_68_perm_0 = const()[name = tensor<string, []>("transpose_68_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
tensor<int32, [4]> transpose_69_perm_0 = const()[name = tensor<string, []>("transpose_69_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
tensor<fp16, [1, 12, 64, 1500]> transpose_77 = transpose(perm = transpose_69_perm_0, x = k_43_cast_fp16)[name = tensor<string, []>("transpose_77")];
tensor<fp16, [1, 12, 1500, 64]> transpose_78 = transpose(perm = transpose_68_perm_0, x = q_43_cast_fp16)[name = tensor<string, []>("transpose_78")];
tensor<fp16, [1, 12, 1500, 1500]> qk_21_cast_fp16 = matmul(transpose_x = qk_21_transpose_x_0, transpose_y = qk_21_transpose_y_0, x = transpose_78, y = transpose_77)[name = tensor<string, []>("qk_21_cast_fp16")];
tensor<fp16, [1, 12, 1500, 1500]> var_1208_cast_fp16 = softmax(axis = var_1144, x = qk_21_cast_fp16)[name = tensor<string, []>("op_1208_cast_fp16")];
tensor<bool, []> var_1210_transpose_x_0 = const()[name = tensor<string, []>("op_1210_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> var_1210_transpose_y_0 = const()[name = tensor<string, []>("op_1210_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [1, 12, 1500, 64]> transpose_79 = transpose(perm = var_1204, x = var_1203_cast_fp16)[name = tensor<string, []>("transpose_79")];
tensor<fp16, [1, 12, 1500, 64]> var_1210_cast_fp16 = matmul(transpose_x = var_1210_transpose_x_0, transpose_y = var_1210_transpose_y_0, x = var_1208_cast_fp16, y = transpose_79)[name = tensor<string, []>("op_1210_cast_fp16")];
tensor<int32, [4]> var_1211 = const()[name = tensor<string, []>("op_1211"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> concat_10 = const()[name = tensor<string, []>("concat_10"), val = tensor<int32, [3]>([1, 1500, 768])];
tensor<fp16, [1, 1500, 12, 64]> transpose_76 = transpose(perm = var_1211, x = var_1210_cast_fp16)[name = tensor<string, []>("transpose_76")];
tensor<fp16, [1, 1500, 768]> x_131_cast_fp16 = reshape(shape = concat_10, x = transpose_76)[name = tensor<string, []>("x_131_cast_fp16")];
tensor<fp16, [768, 768]> var_1216_to_fp16 = const()[name = tensor<string, []>("op_1216_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(151513856)))];
tensor<fp16, [768]> var_1217_to_fp16 = const()[name = tensor<string, []>("op_1217_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152693568)))];
tensor<fp16, [1, 1500, 768]> linear_63_cast_fp16 = linear(bias = var_1217_to_fp16, weight = var_1216_to_fp16, x = x_131_cast_fp16)[name = tensor<string, []>("linear_63_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_133_cast_fp16 = add(x = x_127_cast_fp16, y = linear_63_cast_fp16)[name = tensor<string, []>("x_133_cast_fp16")];
tensor<int32, [1]> var_1224_axes_0 = const()[name = tensor<string, []>("op_1224_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_10_mlp_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_10_mlp_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152695168)))];
tensor<fp16, [768]> blocks_10_mlp_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_10_mlp_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152696768)))];
tensor<fp16, [1, 1500, 768]> var_1224_cast_fp16 = layer_norm(axes = var_1224_axes_0, beta = blocks_10_mlp_ln_bias_to_fp16, epsilon = var_1150_to_fp16, gamma = blocks_10_mlp_ln_weight_to_fp16, x = x_133_cast_fp16)[name = tensor<string, []>("op_1224_cast_fp16")];
tensor<fp16, [3072, 768]> var_1233_to_fp16 = const()[name = tensor<string, []>("op_1233_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(152698368)))];
tensor<fp16, [3072]> var_1234_to_fp16 = const()[name = tensor<string, []>("op_1234_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(157417024)))];
tensor<fp16, [1, 1500, 3072]> linear_64_cast_fp16 = linear(bias = var_1234_to_fp16, weight = var_1233_to_fp16, x = var_1224_cast_fp16)[name = tensor<string, []>("linear_64_cast_fp16")];
tensor<string, []> x_137_mode_0 = const()[name = tensor<string, []>("x_137_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 1500, 3072]> x_137_cast_fp16 = gelu(mode = x_137_mode_0, x = linear_64_cast_fp16)[name = tensor<string, []>("x_137_cast_fp16")];
tensor<fp16, [768, 3072]> var_1239_to_fp16 = const()[name = tensor<string, []>("op_1239_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(157423232)))];
tensor<fp16, [768]> var_1240_to_fp16 = const()[name = tensor<string, []>("op_1240_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(162141888)))];
tensor<fp16, [1, 1500, 768]> linear_65_cast_fp16 = linear(bias = var_1240_to_fp16, weight = var_1239_to_fp16, x = x_137_cast_fp16)[name = tensor<string, []>("linear_65_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_139_cast_fp16 = add(x = x_133_cast_fp16, y = linear_65_cast_fp16)[name = tensor<string, []>("x_139_cast_fp16")];
tensor<int32, []> var_1250 = const()[name = tensor<string, []>("op_1250"), val = tensor<int32, []>(-1)];
tensor<int32, [1]> var_1266_axes_0 = const()[name = tensor<string, []>("op_1266_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_11_attn_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_11_attn_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(162143488)))];
tensor<fp16, [768]> blocks_11_attn_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_11_attn_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(162145088)))];
tensor<fp16, []> var_1256_to_fp16 = const()[name = tensor<string, []>("op_1256_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
tensor<fp16, [1, 1500, 768]> var_1266_cast_fp16 = layer_norm(axes = var_1266_axes_0, beta = blocks_11_attn_ln_bias_to_fp16, epsilon = var_1256_to_fp16, gamma = blocks_11_attn_ln_weight_to_fp16, x = x_139_cast_fp16)[name = tensor<string, []>("op_1266_cast_fp16")];
tensor<fp16, [768, 768]> var_1277_to_fp16 = const()[name = tensor<string, []>("op_1277_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(162146688)))];
tensor<fp16, [768]> var_1278_to_fp16 = const()[name = tensor<string, []>("op_1278_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(163326400)))];
tensor<fp16, [1, 1500, 768]> linear_66_cast_fp16 = linear(bias = var_1278_to_fp16, weight = var_1277_to_fp16, x = var_1266_cast_fp16)[name = tensor<string, []>("linear_66_cast_fp16")];
tensor<fp16, [768, 768]> var_1281_to_fp16 = const()[name = tensor<string, []>("op_1281_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(163328000)))];
tensor<fp16, [1, 1500, 768]> linear_67_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = var_1281_to_fp16, x = var_1266_cast_fp16)[name = tensor<string, []>("linear_67_cast_fp16")];
tensor<fp16, [768, 768]> var_1285_to_fp16 = const()[name = tensor<string, []>("op_1285_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(164507712)))];
tensor<fp16, [768]> var_1286_to_fp16 = const()[name = tensor<string, []>("op_1286_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(165687424)))];
tensor<fp16, [1, 1500, 768]> linear_68_cast_fp16 = linear(bias = var_1286_to_fp16, weight = var_1285_to_fp16, x = var_1266_cast_fp16)[name = tensor<string, []>("linear_68_cast_fp16")];
tensor<int32, [4]> var_1294 = const()[name = tensor<string, []>("op_1294"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_1295_cast_fp16 = reshape(shape = var_1294, x = linear_66_cast_fp16)[name = tensor<string, []>("op_1295_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_106_to_fp16 = const()[name = tensor<string, []>("const_106_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> q_cast_fp16 = mul(x = var_1295_cast_fp16, y = const_106_to_fp16)[name = tensor<string, []>("q_cast_fp16")];
tensor<int32, [4]> var_1301 = const()[name = tensor<string, []>("op_1301"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_1302_cast_fp16 = reshape(shape = var_1301, x = linear_67_cast_fp16)[name = tensor<string, []>("op_1302_cast_fp16")];
tensor<fp16, [1, 1, 1, 1]> const_107_to_fp16 = const()[name = tensor<string, []>("const_107_to_fp16"), val = tensor<fp16, [1, 1, 1, 1]>([[[[0x1.6ap-2]]]])];
tensor<fp16, [1, 1500, 12, 64]> k_cast_fp16 = mul(x = var_1302_cast_fp16, y = const_107_to_fp16)[name = tensor<string, []>("k_cast_fp16")];
tensor<int32, [4]> var_1308 = const()[name = tensor<string, []>("op_1308"), val = tensor<int32, [4]>([1, 1500, 12, -1])];
tensor<fp16, [1, 1500, 12, 64]> var_1309_cast_fp16 = reshape(shape = var_1308, x = linear_68_cast_fp16)[name = tensor<string, []>("op_1309_cast_fp16")];
tensor<int32, [4]> var_1310 = const()[name = tensor<string, []>("op_1310"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<bool, []> qk_transpose_x_0 = const()[name = tensor<string, []>("qk_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> qk_transpose_y_0 = const()[name = tensor<string, []>("qk_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<int32, [4]> transpose_70_perm_0 = const()[name = tensor<string, []>("transpose_70_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
tensor<int32, [4]> transpose_71_perm_0 = const()[name = tensor<string, []>("transpose_71_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
tensor<fp16, [1, 12, 64, 1500]> transpose_73 = transpose(perm = transpose_71_perm_0, x = k_cast_fp16)[name = tensor<string, []>("transpose_73")];
tensor<fp16, [1, 12, 1500, 64]> transpose_74 = transpose(perm = transpose_70_perm_0, x = q_cast_fp16)[name = tensor<string, []>("transpose_74")];
tensor<fp16, [1, 12, 1500, 1500]> qk_cast_fp16 = matmul(transpose_x = qk_transpose_x_0, transpose_y = qk_transpose_y_0, x = transpose_74, y = transpose_73)[name = tensor<string, []>("qk_cast_fp16")];
tensor<fp16, [1, 12, 1500, 1500]> var_1314_cast_fp16 = softmax(axis = var_1250, x = qk_cast_fp16)[name = tensor<string, []>("op_1314_cast_fp16")];
tensor<bool, []> var_1316_transpose_x_0 = const()[name = tensor<string, []>("op_1316_transpose_x_0"), val = tensor<bool, []>(false)];
tensor<bool, []> var_1316_transpose_y_0 = const()[name = tensor<string, []>("op_1316_transpose_y_0"), val = tensor<bool, []>(false)];
tensor<fp16, [1, 12, 1500, 64]> transpose_75 = transpose(perm = var_1310, x = var_1309_cast_fp16)[name = tensor<string, []>("transpose_75")];
tensor<fp16, [1, 12, 1500, 64]> var_1316_cast_fp16 = matmul(transpose_x = var_1316_transpose_x_0, transpose_y = var_1316_transpose_y_0, x = var_1314_cast_fp16, y = transpose_75)[name = tensor<string, []>("op_1316_cast_fp16")];
tensor<int32, [4]> var_1317 = const()[name = tensor<string, []>("op_1317"), val = tensor<int32, [4]>([0, 2, 1, 3])];
tensor<int32, [3]> concat_11 = const()[name = tensor<string, []>("concat_11"), val = tensor<int32, [3]>([1, 1500, 768])];
tensor<fp16, [1, 1500, 12, 64]> transpose_72 = transpose(perm = var_1317, x = var_1316_cast_fp16)[name = tensor<string, []>("transpose_72")];
tensor<fp16, [1, 1500, 768]> x_143_cast_fp16 = reshape(shape = concat_11, x = transpose_72)[name = tensor<string, []>("x_143_cast_fp16")];
tensor<fp16, [768, 768]> var_1322_to_fp16 = const()[name = tensor<string, []>("op_1322_to_fp16"), val = tensor<fp16, [768, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(165689024)))];
tensor<fp16, [768]> var_1323_to_fp16 = const()[name = tensor<string, []>("op_1323_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166868736)))];
tensor<fp16, [1, 1500, 768]> linear_69_cast_fp16 = linear(bias = var_1323_to_fp16, weight = var_1322_to_fp16, x = x_143_cast_fp16)[name = tensor<string, []>("linear_69_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_145_cast_fp16 = add(x = x_139_cast_fp16, y = linear_69_cast_fp16)[name = tensor<string, []>("x_145_cast_fp16")];
tensor<int32, [1]> var_1330_axes_0 = const()[name = tensor<string, []>("op_1330_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> blocks_11_mlp_ln_weight_to_fp16 = const()[name = tensor<string, []>("blocks_11_mlp_ln_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166870336)))];
tensor<fp16, [768]> blocks_11_mlp_ln_bias_to_fp16 = const()[name = tensor<string, []>("blocks_11_mlp_ln_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166871936)))];
tensor<fp16, [1, 1500, 768]> var_1330_cast_fp16 = layer_norm(axes = var_1330_axes_0, beta = blocks_11_mlp_ln_bias_to_fp16, epsilon = var_1256_to_fp16, gamma = blocks_11_mlp_ln_weight_to_fp16, x = x_145_cast_fp16)[name = tensor<string, []>("op_1330_cast_fp16")];
tensor<fp16, [3072, 768]> var_1339_to_fp16 = const()[name = tensor<string, []>("op_1339_to_fp16"), val = tensor<fp16, [3072, 768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166873536)))];
tensor<fp16, [3072]> var_1340_to_fp16 = const()[name = tensor<string, []>("op_1340_to_fp16"), val = tensor<fp16, [3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(171592192)))];
tensor<fp16, [1, 1500, 3072]> linear_70_cast_fp16 = linear(bias = var_1340_to_fp16, weight = var_1339_to_fp16, x = var_1330_cast_fp16)[name = tensor<string, []>("linear_70_cast_fp16")];
tensor<string, []> x_149_mode_0 = const()[name = tensor<string, []>("x_149_mode_0"), val = tensor<string, []>("EXACT")];
tensor<fp16, [1, 1500, 3072]> x_149_cast_fp16 = gelu(mode = x_149_mode_0, x = linear_70_cast_fp16)[name = tensor<string, []>("x_149_cast_fp16")];
tensor<fp16, [768, 3072]> var_1345_to_fp16 = const()[name = tensor<string, []>("op_1345_to_fp16"), val = tensor<fp16, [768, 3072]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(171598400)))];
tensor<fp16, [768]> var_1346_to_fp16 = const()[name = tensor<string, []>("op_1346_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(176317056)))];
tensor<fp16, [1, 1500, 768]> linear_71_cast_fp16 = linear(bias = var_1346_to_fp16, weight = var_1345_to_fp16, x = x_149_cast_fp16)[name = tensor<string, []>("linear_71_cast_fp16")];
tensor<fp16, [1, 1500, 768]> x_cast_fp16 = add(x = x_145_cast_fp16, y = linear_71_cast_fp16)[name = tensor<string, []>("x_cast_fp16")];
tensor<int32, [1]> var_1359_axes_0 = const()[name = tensor<string, []>("op_1359_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [768]> ln_post_weight_to_fp16 = const()[name = tensor<string, []>("ln_post_weight_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(176318656)))];
tensor<fp16, [768]> ln_post_bias_to_fp16 = const()[name = tensor<string, []>("ln_post_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(176320256)))];
tensor<fp16, []> var_1350_to_fp16 = const()[name = tensor<string, []>("op_1350_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
tensor<fp16, [1, 1500, 768]> output = layer_norm(axes = var_1359_axes_0, beta = ln_post_bias_to_fp16, epsilon = var_1350_to_fp16, gamma = ln_post_weight_to_fp16, x = x_cast_fp16)[name = tensor<string, []>("op_1359_cast_fp16")];
} -> (output);
}