Add 49 files

astype_copy.pkl

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+size 716

codette.metadata.v9.bin

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+oid sha256:c645d26f746c7f66ec0be9ddac5f158008f8626b85b32aaf4ed8b530753f41aa
+size 1765

codette.projects.v9.bin

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+oid sha256:733fef2d250dc4691c54275301cc429928a9f17dc0b44051b1efee6538ddba6c
+size 74518

codette.strings.v9.bin

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+oid sha256:bc83c69937b5eba9e6770ee23148ade429e801f4363c3853ca78aa32efa7926e
+size 174680

codettev3.zip

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+oid sha256:e19bf1008b054e1998d082e21ac08325de6b3a85ce563ccce891ce468c14d673
+size 637284

deploy_space_action.yaml

@@ -0,0 +1,28 @@
+name: Run Python script
+
+on:
+  push:
+    branches:
+      - $branch
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+    - name: Checkout
+      uses: actions/checkout@v2
+
+    - name: Set up Python
+      uses: actions/setup-python@v2
+      with:
+        python-version: '3.9'
+
+    - name: Install Gradio
+      run: python -m pip install gradio
+
+    - name: Log in to Hugging Face
+      run: python -c 'import huggingface_hub; huggingface_hub.login(token="${{ secrets.hf_token }}")'
+
+    - name: Deploy to Spaces
+      run: gradio deploy

deprecated.yaml

@@ -0,0 +1,134 @@
+# Deprecated function signatures. These are exposed in Python, but not included
+# in the error message suggestions.
+
+- name: add(Tensor self, Scalar alpha, Tensor other) -> Tensor
+  aten: add(self, other, alpha)
+
+- name: add_(Tensor(a!) self, Scalar alpha, Tensor other) -> Tensor(a!)
+  aten: add_(self, other, alpha)
+
+- name: add(Tensor self, Scalar alpha, Tensor other, *, Tensor(a!) out) -> Tensor(a!)
+  aten: add_out(out, self, other, alpha)
+
+- name: addbmm(Scalar beta, Tensor self, Scalar alpha, Tensor batch1, Tensor batch2) -> Tensor
+  aten: addbmm(self, batch1, batch2, beta, alpha)
+
+- name: addbmm_(Scalar beta, Tensor(a!) self, Scalar alpha, Tensor batch1, Tensor batch2) -> Tensor(a!)
+  aten: addbmm_(self, batch1, batch2, beta, alpha)
+
+- name: addbmm(Scalar beta, Tensor self, Scalar alpha, Tensor batch1, Tensor batch2, *, Tensor(a!) out) -> Tensor(a!)
+  aten: addbmm_out(out, self, batch1, batch2, beta, alpha)
+
+- name: addbmm(Scalar beta, Tensor self, Tensor batch1, Tensor batch2) -> Tensor
+  aten: addbmm(self, batch1, batch2, beta, 1)
+
+- name: addbmm_(Scalar beta, Tensor(a!) self, Tensor batch1, Tensor batch2) -> Tensor(a!)
+  aten: addbmm_(self, batch1, batch2, beta, 1)
+
+- name: addbmm(Scalar beta, Tensor self, Tensor batch1, Tensor batch2, *, Tensor(a!) out) -> Tensor(a!)
+  aten: addbmm_out(out, self, batch1, batch2, beta, 1)
+
+- name: addcdiv(Tensor self, Scalar value, Tensor tensor1, Tensor tensor2) -> Tensor
+  aten: addcdiv(self, tensor1, tensor2, value)
+
+- name: addcdiv_(Tensor(a!) self, Scalar value, Tensor tensor1, Tensor tensor2) -> Tensor(a!)
+  aten: addcdiv_(self, tensor1, tensor2, value)
+
+- name: addcdiv(Tensor self, Scalar value, Tensor tensor1, Tensor tensor2, *, Tensor(a!) out) -> Tensor(a!)
+  aten: addcdiv_out(out, self, tensor1, tensor2, value)
+
+- name: addcmul(Tensor self, Scalar value, Tensor tensor1, Tensor tensor2) -> Tensor
+  aten: addcmul(self, tensor1, tensor2, value)
+
+- name: addcmul_(Tensor(a!) self, Scalar value, Tensor tensor1, Tensor tensor2) -> Tensor(a!)
+  aten: addcmul_(self, tensor1, tensor2, value)
+
+- name: addcmul(Tensor self, Scalar value, Tensor tensor1, Tensor tensor2, *, Tensor(a!) out) -> Tensor(a!)
+  aten: addcmul_out(out, self, tensor1, tensor2, value)
+
+- name: addmm(Scalar beta, Tensor self, Scalar alpha, Tensor mat1, Tensor mat2) -> Tensor
+  aten: addmm(self, mat1, mat2, beta, alpha)
+
+- name: addmm_(Scalar beta, Tensor(a!) self, Scalar alpha, Tensor mat1, Tensor mat2) -> Tensor(a!)
+  aten: addmm_(self, mat1, mat2, beta, alpha)
+
+- name: addmm(Scalar beta, Tensor self, Scalar alpha, Tensor mat1, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!)
+  aten: addmm_out(out, self, mat1, mat2, beta, alpha)
+
+- name: addmm(Scalar beta, Tensor self, Tensor mat1, Tensor mat2) -> Tensor
+  aten: addmm(self, mat1, mat2, beta, 1)
+
+- name: addmm_(Scalar beta, Tensor(a!) self, Tensor mat1, Tensor mat2) -> Tensor(a!)
+  aten: addmm_(self, mat1, mat2, beta, 1)
+
+- name: addmm(Scalar beta, Tensor self, Tensor mat1, Tensor mat2, *, Tensor(a!) out) -> Tensor(a!)
+  aten: addmm_out(out, self, mat1, mat2, beta, 1)
+
+- name: sspaddmm(Scalar beta, Tensor self, Scalar alpha, Tensor mat1, Tensor mat2) -> Tensor
+  aten: sspaddmm(self, mat1, mat2, beta, alpha)
+
+- name: sspaddmm(Scalar beta, Tensor self, Tensor mat1, Tensor mat2) -> Tensor
+  aten: sspaddmm(self, mat1, mat2, beta, 1)
+
+- name: addmv(Scalar beta, Tensor self, Scalar alpha, Tensor mat, Tensor vec) -> Tensor
+  aten: addmv(self, mat, vec, beta, alpha)
+
+- name: addmv_(Scalar beta, Tensor(a!) self, Scalar alpha, Tensor mat, Tensor vec) -> Tensor(a!)
+  aten: addmv_(self, mat, vec, beta, alpha)
+
+- name: addmv(Scalar beta, Tensor self, Scalar alpha, Tensor mat, Tensor vec, *, Tensor(a!) out) -> Tensor(a!)
+  aten: addmv_out(out, self, mat, vec, beta, alpha)
+
+- name: addmv(Scalar beta, Tensor self, Tensor mat, Tensor vec) -> Tensor
+  aten: addmv(self, mat, vec, beta, 1)
+
+- name: addmv_(Scalar beta, Tensor(a!) self, Tensor mat, Tensor vec) -> Tensor(a!)
+  aten: addmv_(self, mat, vec, beta, 1)
+
+- name: addmv(Scalar beta, Tensor self, Tensor mat, Tensor vec, *, Tensor(a!) out) -> Tensor(a!)
+  aten: addmv_out(out, self, mat, vec, beta, 1)
+
+- name: addr(Scalar beta, Tensor self, Scalar alpha, Tensor vec1, Tensor vec2) -> Tensor
+  aten: addr(self, vec1, vec2, beta, alpha)
+
+- name: addr_(Scalar beta, Tensor(a!) self, Scalar alpha, Tensor vec1, Tensor vec2) -> Tensor(a!)
+  aten: addr_(self, vec1, vec2, beta, alpha)
+
+- name: addr(Scalar beta, Tensor self, Scalar alpha, Tensor vec1, Tensor vec2, *, Tensor(a!) out) -> Tensor(a!)
+  aten: addr_out(out, self, vec1, vec2, beta, alpha)
+
+- name: addr(Scalar beta, Tensor self, Tensor vec1, Tensor vec2) -> Tensor
+  aten: addr(self, vec1, vec2, beta, 1)
+
+- name: addr_(Scalar beta, Tensor(a!) self, Tensor vec1, Tensor vec2) -> Tensor(a!)
+  aten: addr_(self, vec1, vec2, beta, 1)
+
+- name: addr(Scalar beta, Tensor self, Tensor vec1, Tensor vec2, *, Tensor(a!) out) -> Tensor(a!)
+  aten: addr_out(out, self, vec1, vec2, beta, 1)
+
+- name: baddbmm(Scalar beta, Tensor self, Scalar alpha, Tensor batch1, Tensor batch2) -> Tensor
+  aten: baddbmm(self, batch1, batch2, beta, alpha)
+
+- name: baddbmm_(Scalar beta, Tensor(a!) self, Scalar alpha, Tensor batch1, Tensor batch2) -> Tensor(a!)
+  aten: baddbmm_(self, batch1, batch2, beta, alpha)
+
+- name: baddbmm(Scalar beta, Tensor self, Scalar alpha, Tensor batch1, Tensor batch2, *, Tensor(a!) out) -> Tensor(a!)
+  aten: baddbmm_out(out, self, batch1, batch2, beta, alpha)
+
+- name: baddbmm(Scalar beta, Tensor self, Tensor batch1, Tensor batch2) -> Tensor
+  aten: baddbmm(self, batch1, batch2, beta, 1)
+
+- name: baddbmm_(Scalar beta, Tensor(a!) self, Tensor batch1, Tensor batch2) -> Tensor(a!)
+  aten: baddbmm_(self, batch1, batch2, beta, 1)
+
+- name: baddbmm(Scalar beta, Tensor self, Tensor batch1, Tensor batch2, *, Tensor(a!) out) -> Tensor(a!)
+  aten: baddbmm_out(out, self, batch1, batch2, beta, 1)
+
+- name: sub(Tensor self, Scalar alpha, Tensor other) -> Tensor
+  aten: sub(self, other, alpha)
+
+- name: sub_(Tensor(a!) self, Scalar alpha, Tensor other) -> Tensor(a!)
+  aten: sub_(self, other, alpha)
+
+- name: sub(Tensor self, Scalar alpha, Tensor other, *, Tensor(a!) out) -> Tensor(a!)
+  aten: sub_out(out, self, other, alpha)

joblib_0.10.0_pickle_py27_np17.pkl

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joblib_0.10.0_pickle_py33_np18.pkl

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joblib_0.10.0_pickle_py34_np19.pkl

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joblib_0.10.0_pickle_py35_np19.pkl

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joblib_0.11.0_pickle_py36_np111.pkl

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joblib_0.9.2_pickle_py27_np16.pkl

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joblib_0.9.2_pickle_py27_np17.pkl

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joblib_0.9.2_pickle_py33_np18.pkl

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joblib_0.9.2_pickle_py34_np19.pkl

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joblib_0.9.2_pickle_py35_np19.pkl

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language-model.lm.bin

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log_config.yml

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+version: 1
+disable_existing_loggers: False
+formatters:
+  default:
+    "()": uvicorn.logging.DefaultFormatter
+    format: '%(levelprefix)s [%(asctime)s] %(message)s'
+    use_colors: null
+    datefmt: '%d-%m-%Y %H:%M:%S'
+  access:
+    "()": uvicorn.logging.AccessFormatter
+    format: '%(levelprefix)s [%(asctime)s] %(client_addr)s - "%(request_line)s" %(status_code)s'
+    datefmt: '%d-%m-%Y %H:%M:%S'
+handlers:
+  default:
+    formatter: default
+    class: logging.StreamHandler
+    stream: ext://sys.stderr
+  access:
+    formatter: access
+    class: logging.StreamHandler
+    stream: ext://sys.stdout
+  console:
+    class: logging.StreamHandler
+    stream: ext://sys.stdout
+    formatter: default
+  file:
+    class : logging.handlers.RotatingFileHandler
+    filename: chroma.log
+    formatter: default
+loggers:
+  root:
+    level: WARN
+    handlers: [console, file]
+  chromadb:
+    level: DEBUG
+  uvicorn:
+    level: INFO

logreg_iris.onnx

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mul_1.onnx

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my-test-package.zip

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nev3.zip

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port.yaml

@@ -0,0 +1,48 @@
+- package: markdown-it/markdown-it
+  version: 13.0.1
+  commit: e843acc9edad115cbf8cf85e676443f01658be08
+  date: May 3, 2022
+  notes:
+    - Rename variables that use python built-in names, e.g.
+      - `max` -> `maximum`
+      - `len` -> `length`
+      - `str` -> `string`
+    - |
+      Convert JS `for` loops to `while` loops
+      this is generally the main difference between the codes,
+      because in python you can't do e.g. `for {i=1;i<x;i++} {}`
+    - |
+      `env` is a common Python dictionary, and so does not have attribute access to keys,
+      as with JavaScript dictionaries.
+      `options` have attribute access only to core markdownit configuration options
+    - |
+      `Token.attrs` is a dictionary, instead of a list of lists.
+      Upstream the list format is only used to guarantee order: https://github.com/markdown-it/markdown-it/issues/142,
+      but in Python 3.7+ order of dictionaries is guaranteed.
+      One should anyhow use the `attrGet`, `attrSet`, `attrPush` and `attrJoin` methods
+      to manipulate `Token.attrs`, which have an identical signature to those upstream.
+    - Use python version of `charCodeAt`
+    - |
+      Use `str` units instead of `int`s to represent Unicode codepoints.
+      This provides a significant performance boost
+    - |
+      In markdown_it/rules_block/reference.py,
+      record line range in state.env["references"] and add state.env["duplicate_refs"]
+      This is to allow renderers to report on issues regarding references
+    - |
+      The `MarkdownIt.__init__` signature is slightly different for updating options,
+      since you must always specify the config first, e.g.
+      use `MarkdownIt("commonmark", {"html": False})` instead of `MarkdownIt({"html": False})`
+    - The default configuration preset for `MarkdownIt` is "commonmark" not "default"
+    - Allow custom renderer to be passed to `MarkdownIt`
+    - |
+      change render method signatures
+      `func(tokens, idx, options, env, slf)` to
+      `func(self, tokens, idx, options, env)`
+    - |
+      Extensions add render methods by format
+      `MarkdownIt.add_render_rule(name, function, fmt="html")`,
+      rather than `MarkdownIt.renderer.rules[name] = function`
+      and renderers should declare a class property `__output__ = "html"`.
+      This allows for extensibility to more than just HTML renderers
+    - inline tokens in tables are assigned a map (this is helpful for propagation to children)

schema.yaml

@@ -0,0 +1,462 @@
+# @generated by update_schema.py
+# checksum<<9e3a8f9389cd89b981fa654e4bf6ebc544f1696f9cac84818d60424143426f30>>
+Argument:
+  kind: union
+  fields:
+    as_none:
+      type: bool
+    as_tensor:
+      type: TensorArgument
+    as_tensors:
+      type: List[TensorArgument]
+    as_int:
+      type: int
+    as_ints:
+      type: List[int]
+    as_float:
+      type: float
+    as_floats:
+      type: List[float]
+    as_string:
+      type: str
+    as_strings:
+      type: List[str]
+    as_sym_int:
+      type: SymIntArgument
+    as_sym_ints:
+      type: List[SymIntArgument]
+    as_scalar_type:
+      type: ScalarType
+    as_memory_format:
+      type: MemoryFormat
+    as_layout:
+      type: Layout
+    as_device:
+      type: Device
+    as_bool:
+      type: bool
+    as_bools:
+      type: List[bool]
+    as_sym_bool:
+      type: SymBoolArgument
+    as_sym_bools:
+      type: List[SymBoolArgument]
+    as_graph:
+      type: GraphArgument
+    as_optional_tensors:
+      type: List[OptionalTensorArgument]
+    as_custom_obj:
+      type: CustomObjArgument
+    as_operator:
+      type: str
+    as_sym_float:
+      type: SymFloatArgument
+    as_sym_floats:
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+BufferMutationSpec:
+  kind: struct
+  fields:
+    arg:
+      type: TensorArgument
+    buffer_name:
+      type: str
+ConstantValue:
+  kind: union
+  fields:
+    as_none:
+      type: bool
+    as_int:
+      type: int
+    as_float:
+      type: float
+    as_string:
+      type: str
+    as_bool:
+      type: bool
+CustomObjArgument:
+  kind: struct
+  fields:
+    name:
+      type: str
+    class_fqn:
+      type: str
+Device:
+  kind: struct
+  fields:
+    type:
+      type: str
+    index:
+      type: Optional[int]
+      default: None
+ExportedProgram:
+  kind: struct
+  fields:
+    graph_module:
+      type: GraphModule
+    opset_version:
+      type: Dict[str, int]
+    range_constraints:
+      type: Dict[str, RangeConstraint]
+    schema_version:
+      type: SchemaVersion
+    verifiers:
+      type: List[str]
+      default: '[]'
+    torch_version:
+      type: str
+      default: <=2.4
+GradientToParameterSpec:
+  kind: struct
+  fields:
+    arg:
+      type: TensorArgument
+    parameter_name:
+      type: str
+GradientToUserInputSpec:
+  kind: struct
+  fields:
+    arg:
+      type: TensorArgument
+    user_input_name:
+      type: str
+Graph:
+  kind: struct
+  fields:
+    inputs:
+      type: List[Argument]
+    outputs:
+      type: List[Argument]
+    nodes:
+      type: List[Node]
+    tensor_values:
+      type: Dict[str, TensorMeta]
+    sym_int_values:
+      type: Dict[str, SymInt]
+    sym_bool_values:
+      type: Dict[str, SymBool]
+    is_single_tensor_return:
+      type: bool
+      default: 'False'
+    custom_obj_values:
+      type: Dict[str, CustomObjArgument]
+      default: '{}'
+    sym_float_values:
+      type: Dict[str, SymFloat]
+      default: '{}'
+GraphArgument:
+  kind: struct
+  fields:
+    name:
+      type: str
+    graph:
+      type: Graph
+GraphModule:
+  kind: struct
+  fields:
+    graph:
+      type: Graph
+    signature:
+      type: GraphSignature
+    module_call_graph:
+      type: List[ModuleCallEntry]
+    metadata:
+      type: Dict[str, str]
+      default: '{}'
+GraphSignature:
+  kind: struct
+  fields:
+    input_specs:
+      type: List[InputSpec]
+    output_specs:
+      type: List[OutputSpec]
+InputSpec:
+  kind: union
+  fields:
+    user_input:
+      type: UserInputSpec
+    parameter:
+      type: InputToParameterSpec
+    buffer:
+      type: InputToBufferSpec
+    tensor_constant:
+      type: InputToTensorConstantSpec
+    custom_obj:
+      type: InputToCustomObjSpec
+    token:
+      type: InputTokenSpec
+    constant_input:
+      type: InputToConstantInputSpec
+InputToBufferSpec:
+  kind: struct
+  fields:
+    arg:
+      type: TensorArgument
+    buffer_name:
+      type: str
+    persistent:
+      type: bool
+InputToConstantInputSpec:
+  kind: struct
+  fields:
+    name:
+      type: str
+    value:
+      type: ConstantValue
+InputToCustomObjSpec:
+  kind: struct
+  fields:
+    arg:
+      type: CustomObjArgument
+    custom_obj_name:
+      type: str
+InputToParameterSpec:
+  kind: struct
+  fields:
+    arg:
+      type: TensorArgument
+    parameter_name:
+      type: str
+InputToTensorConstantSpec:
+  kind: struct
+  fields:
+    arg:
+      type: TensorArgument
+    tensor_constant_name:
+      type: str
+InputTokenSpec:
+  kind: struct
+  fields:
+    arg:
+      type: TokenArgument
+Layout:
+  kind: enum
+  fields:
+    Unknown: 0
+    SparseCoo: 1
+    SparseCsr: 2
+    SparseCsc: 3
+    SparseBsr: 4
+    SparseBsc: 5
+    _mkldnn: 6
+    Strided: 7
+LossOutputSpec:
+  kind: struct
+  fields:
+    arg:
+      type: TensorArgument
+MemoryFormat:
+  kind: enum
+  fields:
+    Unknown: 0
+    ContiguousFormat: 1
+    ChannelsLast: 2
+    ChannelsLast3d: 3
+    PreserveFormat: 4
+ModuleCallEntry:
+  kind: struct
+  fields:
+    fqn:
+      type: str
+    signature:
+      type: Optional[ModuleCallSignature]
+      default: None
+ModuleCallSignature:
+  kind: struct
+  fields:
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+      type: List[Argument]
+    outputs:
+      type: List[Argument]
+    in_spec:
+      type: str
+    out_spec:
+      type: str
+    forward_arg_names:
+      type: Optional[List[str]]
+      default: None
+NamedArgument:
+  kind: struct
+  fields:
+    name:
+      type: str
+    arg:
+      type: Argument
+Node:
+  kind: struct
+  fields:
+    target:
+      type: str
+    inputs:
+      type: List[NamedArgument]
+    outputs:
+      type: List[Argument]
+    metadata:
+      type: Dict[str, str]
+OptionalTensorArgument:
+  kind: union
+  fields:
+    as_tensor:
+      type: TensorArgument
+    as_none:
+      type: bool
+OutputSpec:
+  kind: union
+  fields:
+    user_output:
+      type: UserOutputSpec
+    loss_output:
+      type: LossOutputSpec
+    buffer_mutation:
+      type: BufferMutationSpec
+    gradient_to_parameter:
+      type: GradientToParameterSpec
+    gradient_to_user_input:
+      type: GradientToUserInputSpec
+    user_input_mutation:
+      type: UserInputMutationSpec
+    token:
+      type: OutputTokenSpec
+OutputTokenSpec:
+  kind: struct
+  fields:
+    arg:
+      type: TokenArgument
+RangeConstraint:
+  kind: struct
+  fields:
+    min_val:
+      type: Optional[int]
+    max_val:
+      type: Optional[int]
+ScalarType:
+  kind: enum
+  fields:
+    UNKNOWN: 0
+    BYTE: 1
+    CHAR: 2
+    SHORT: 3
+    INT: 4
+    LONG: 5
+    HALF: 6
+    FLOAT: 7
+    DOUBLE: 8
+    COMPLEXHALF: 9
+    COMPLEXFLOAT: 10
+    COMPLEXDOUBLE: 11
+    BOOL: 12
+    BFLOAT16: 13
+    UINT16: 28
+SchemaVersion:
+  kind: struct
+  fields:
+    major:
+      type: int
+    minor:
+      type: int
+SymBool:
+  kind: union
+  fields:
+    as_expr:
+      type: SymExpr
+    as_bool:
+      type: bool
+SymBoolArgument:
+  kind: union
+  fields:
+    as_name:
+      type: str
+    as_bool:
+      type: bool
+SymExpr:
+  kind: struct
+  fields:
+    expr_str:
+      type: str
+    hint:
+      type: Optional[SymExprHint]
+      default: None
+SymExprHint:
+  kind: union
+  fields:
+    as_int:
+      type: int
+    as_bool:
+      type: bool
+    as_float:
+      type: float
+SymFloat:
+  kind: union
+  fields:
+    as_expr:
+      type: SymExpr
+    as_float:
+      type: float
+SymFloatArgument:
+  kind: union
+  fields:
+    as_name:
+      type: str
+    as_float:
+      type: float
+SymInt:
+  kind: union
+  fields:
+    as_expr:
+      type: SymExpr
+    as_int:
+      type: int
+SymIntArgument:
+  kind: union
+  fields:
+    as_name:
+      type: str
+    as_int:
+      type: int
+TensorArgument:
+  kind: struct
+  fields:
+    name:
+      type: str
+TensorMeta:
+  kind: struct
+  fields:
+    dtype:
+      type: ScalarType
+    sizes:
+      type: List[SymInt]
+    requires_grad:
+      type: bool
+    device:
+      type: Device
+    strides:
+      type: List[SymInt]
+    storage_offset:
+      type: SymInt
+    layout:
+      type: Layout
+TokenArgument:
+  kind: struct
+  fields:
+    name:
+      type: str
+UserInputMutationSpec:
+  kind: struct
+  fields:
+    arg:
+      type: TensorArgument
+    user_input_name:
+      type: str
+UserInputSpec:
+  kind: struct
+  fields:
+    arg:
+      type: Argument
+UserOutputSpec:
+  kind: struct
+  fields:
+    arg:
+      type: Argument
+SCHEMA_VERSION:
+- 8
+- 2
+TREESPEC_VERSION: 1

sigmoid.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5340aba67a7e3475162ad794378af55f1718f55f9a5d74b4af60ecc7f7a624b6
+size 103

tags.yaml

@@ -0,0 +1,80 @@
+# This yaml file contains all the possible tags that can be defined in `tags` in `native_functions.yaml`
+
+- tag: inplace_view
+  desc: |
+          This tag indicates if an operator *only* modifies the tensor metadata
+- tag: pt2_compliant_tag
+  desc: |
+          This tag indicates if the operator is guaranteed to
+          work with the PT2 compilation APIs (torch.compile,
+          torch.export, etc). If you add this tag to an
+          operator, please use
+          `torch.testing._internal.optest.opcheck` to test that
+          the operator has been registered correctly and
+          works with torch.compile
+- tag: view_copy
+  desc: |
+          This tag indicates operators that are *_copy* variants
+          of view/aliasing operators. If an operator has a view_copy tag,
+          then it should have the name {op}_copy, where {op} is a view operator.
+- tag: dynamic_output_shape
+  desc: |
+          This tag indicates if an operator's output's shape depends on input Tensor
+          data.
+- tag: data_dependent_output
+  desc: |
+          Operator has a non-Tensor output whose value is dependent on the data
+          of Tensor inputs.  Among other things, this implies that this operator
+          cannot be run with meta tensor (since data is not available), nor
+          can it be symbolically traced.
+- tag: generated
+  desc: |
+          This tag indicates that the operator doesn't have an explicit entry in
+          native_functions.yaml, and instead was generated automatically by the codegen.
+- tag: nondeterministic_seeded
+  desc: |
+          This tag indicates if an operator is nondeterministically seeded
+          (i.e., is random) such that the operator intentionally produces
+          different results when run twice on the same inputs, but this randomness
+          is controlled by a Generator which, if reseeded would give you the
+          same result.
+- tag: nondeterministic_bitwise
+  desc: |
+          This tag indicates if an operator doesn't guarantee bitwise equivalence
+          across different runs of an operator with identical inputs.
+- tag: needs_fixed_stride_order
+  desc: |
+          This tag indicates that the operator should be passed Tensors following
+          the same stride permutation as observed in eager when compiled in inductor.
+          Only one of {needs_fixed_stride_order, flexible_layout} can apply; if
+          multiple are assigned then we assume the most restrictive one.
+- tag: flexible_layout
+  desc: |
+          This tag indicates that the custom operator can accept inputs with varying
+          strides/storage_offset and that when compiled, Inductor is allowed to change
+          the strides/storage_offset of inputs to the custom operator.
+          Only one of {needs_fixed_stride_order, flexible_layout} can apply; if
+          multiple are assigned then we assume the most restrictive one.
+
+# NOTE [Core ATen Ops]
+- tag: core
+  desc: |
+          Core aten ops is a subset of aten ops that remains after aten-to-aten decomposition and
+          functionalization pass. Core aten ops are fully functional and adhere to single static
+          assignment (SSA): this implies there will be no `inplace` or `_out` variants in this opset.
+          This opset is designed to serve as the functional IR to interface with compiler backends.
+          In contrast to primTorch, core aten opset doesn't decompose ops into explicit
+          type promotion and broadcasting ops.
+          Core aten ops is also effectively the opset produced by torchdynamo.export(aten_graph=True),
+          and thus can be used as an opset for export purpose.
+- tag: pointwise
+  desc: |
+          Pointwise operators are operators where each element of the output is computed only by accessing
+          the corresponding element of all the broadcasted inputs. The output shape will be the broadcasted
+          shape of the inputs.
+- tag: maybe_aliasing_or_mutating
+  desc: |
+          For some ops, we can't statically determine whether the op is functional or not. Note that this is only
+          relevant to CIA ops that decompose before functionalization/autograd. It is useful to
+          know this information for export as we would want to decompose these ops as they are unsafe to be
+          preserved.

teamsapp.local.yml

@@ -0,0 +1,79 @@
+# yaml-language-server: $schema=https://aka.ms/teams-toolkit/v1.7/yaml.schema.json
+# Visit https://aka.ms/teamsfx-v5.0-guide for details on this file
+# Visit https://aka.ms/teamsfx-actions for details on actions
+version: v1.7
+
+provision:
+  # Creates a Teams app
+  - uses: teamsApp/create
+    with:
+      # Teams app name
+      name: codette${{APP_NAME_SUFFIX}}
+    # Write the information of created resources into environment file for
+    # the specified environment variable(s).
+    writeToEnvironmentFile:
+      teamsAppId: TEAMS_APP_ID
+
+  # Create or reuse an existing Microsoft Entra application for bot.
+  - uses: aadApp/create
+    with:
+      # The Microsoft Entra application's display name
+      name: codette${{APP_NAME_SUFFIX}}
+      generateClientSecret: true
+      signInAudience: AzureADMultipleOrgs
+    writeToEnvironmentFile:
+      # The Microsoft Entra application's client id created for bot.
+      clientId: BOT_ID
+      # The Microsoft Entra application's client secret created for bot.
+      clientSecret: SECRET_BOT_PASSWORD
+      # The Microsoft Entra application's object id created for bot.
+      objectId: BOT_OBJECT_ID
+
+  # Generate runtime appsettings to JSON file
+  - uses: file/createOrUpdateJsonFile
+    with:
+      target: ../codette/appsettings.Development.json
+      content:
+        BOT_TYPE: 'MultiTenant'
+        BOT_ID: ${{BOT_ID}}
+        BOT_PASSWORD: ${{SECRET_BOT_PASSWORD}}
+        Azure:
+          OpenAIApiKey: ${{SECRET_AZURE_OPENAI_API_KEY}}
+          OpenAIEndpoint: ${{AZURE_OPENAI_ENDPOINT}}
+          OpenAIDeploymentName: ${{AZURE_OPENAI_DEPLOYMENT_NAME}}
+
+  # Create or update the bot registration on dev.botframework.com
+  - uses: botFramework/create
+    with:
+      botId: ${{BOT_ID}}
+      name: codette
+      messagingEndpoint: ${{BOT_ENDPOINT}}/api/messages
+      description: ""
+      channels:
+        - name: msteams
+  # Validate using manifest schema
+  - uses: teamsApp/validateManifest
+    with:
+      # Path to manifest template
+      manifestPath: ./appPackage/manifest.json
+  # Build Teams app package with latest env value
+  - uses: teamsApp/zipAppPackage
+    with:
+      # Path to manifest template
+      manifestPath: ./appPackage/manifest.json
+      outputZipPath: ./appPackage/build/appPackage.${{TEAMSFX_ENV}}.zip
+      outputFolder: ./appPackage/build
+  # Validate app package using validation rules
+  - uses: teamsApp/validateAppPackage
+    with:
+      # Relative path to this file. This is the path for built zip file.
+      appPackagePath: ./appPackage/build/appPackage.${{TEAMSFX_ENV}}.zip
+
+  # Apply the Teams app manifest to an existing Teams app in
+  # Teams Developer Portal.
+  # Will use the app id in manifest file to determine which Teams app to update.
+  - uses: teamsApp/update
+    with:
+      # Relative path to this file. This is the path for built zip file.
+      appPackagePath: ./appPackage/build/appPackage.${{TEAMSFX_ENV}}.zip
+

teamsapp.yml

@@ -0,0 +1,87 @@
+# yaml-language-server: $schema=https://aka.ms/teams-toolkit/v1.7/yaml.schema.json
+# Visit https://aka.ms/teamsfx-v5.0-guide for details on this file
+# Visit https://aka.ms/teamsfx-actions for details on actions
+version: v1.7
+
+environmentFolderPath: ./env
+
+# Triggered when 'teamsapp provision' is executed
+provision:
+  # Creates a Teams app
+  - uses: teamsApp/create
+    with:
+      # Teams app name
+      name: codette${{APP_NAME_SUFFIX}}
+    # Write the information of created resources into environment file for
+    # the specified environment variable(s).
+    writeToEnvironmentFile:
+      teamsAppId: TEAMS_APP_ID
+
+  - uses: arm/deploy # Deploy given ARM templates parallelly.
+    with:
+      # AZURE_SUBSCRIPTION_ID is a built-in environment variable,
+      # if its value is empty, TeamsFx will prompt you to select a subscription.
+      # Referencing other environment variables with empty values
+      # will skip the subscription selection prompt.
+      subscriptionId: ${{AZURE_SUBSCRIPTION_ID}}
+      # AZURE_RESOURCE_GROUP_NAME is a built-in environment variable,
+      # if its value is empty, TeamsFx will prompt you to select or create one
+      # resource group.
+      # Referencing other environment variables with empty values
+      # will skip the resource group selection prompt.
+      resourceGroupName: ${{AZURE_RESOURCE_GROUP_NAME}}
+      templates:
+        - path: ./infra/azure.bicep # Relative path to this file
+          # Relative path to this yaml file.
+          # Placeholders will be replaced with corresponding environment
+          # variable before ARM deployment.
+          parameters: ./infra/azure.parameters.json
+          # Required when deploying ARM template
+          deploymentName: Create-resources-for-bot
+      # Teams Toolkit will download this bicep CLI version from github for you,
+      # will use bicep CLI in PATH if you remove this config.
+      bicepCliVersion: v0.9.1
+  # Validate using manifest schema
+  - uses: teamsApp/validateManifest
+    with:
+      # Path to manifest template
+      manifestPath: ./appPackage/manifest.json
+  # Build Teams app package with latest env value
+  - uses: teamsApp/zipAppPackage
+    with:
+      # Path to manifest template
+      manifestPath: ./appPackage/manifest.json
+      outputZipPath: ./appPackage/build/appPackage.${{TEAMSFX_ENV}}.zip
+      outputFolder: ./appPackage/build
+  # Validate app package using validation rules
+  - uses: teamsApp/validateAppPackage
+    with:
+      # Relative path to this file. This is the path for built zip file.
+      appPackagePath: ./appPackage/build/appPackage.${{TEAMSFX_ENV}}.zip
+  # Apply the Teams app manifest to an existing Teams app in
+  # Teams Developer Portal.
+  # Will use the app id in manifest file to determine which Teams app to update.
+  - uses: teamsApp/update
+    with:
+      # Relative path to this file. This is the path for built zip file.
+      appPackagePath: ./appPackage/build/appPackage.${{TEAMSFX_ENV}}.zip
+
+# Triggered when 'teamsapp deploy' is executed
+deploy:
+  - uses: cli/runDotnetCommand
+    with:
+      args: publish --configuration Release codette.csproj
+      workingDirectory: ../codette
+  # Deploy your application to Azure App Service using the zip deploy feature.
+  # For additional details, refer to https://aka.ms/zip-deploy-to-app-services.
+  - uses: azureAppService/zipDeploy
+    with:
+      # Deploy base folder
+      artifactFolder: bin/Release/net8.0/publish
+      # The resource id of the cloud resource to be deployed to.
+      # This key will be generated by arm/deploy action automatically.
+      # You can replace it with your existing Azure Resource id
+      # or add it to your environment variable file.
+      resourceId: ${{BOT_AZURE_APP_SERVICE_RESOURCE_ID}}
+      workingDirectory: ../codette
+projectId: aed51bd9-1779-40ba-b1ea-6d41c7319608