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# Copyright 2024 Big Vision Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Utils for GIVT stage I and II trainers."""
from typing import Any
import jax
import jax.numpy as jnp
def unbin_depth(
depth: jax.Array,
*,
min_depth: float,
max_depth: float,
num_bins: int,
) -> jax.Array:
"""Transform a depth map with binned values into a float-valued depth map.
Args:
depth: Depth map whose binned values are encoded in one-hot fashion along
the last dimension.
min_depth: Minimum binned depth value.
max_depth: Maximum value of binned depth.
num_bins: Number of depth bins.
Returns:
Float-valued depth map.
"""
depth = jnp.argmax(depth, axis=-1)
depth = depth.astype(jnp.float32) + 0.5 # Undoes floor in expectation.
depth /= num_bins
return depth * (max_depth - min_depth) + min_depth
def get_local_rng(
seed: int | jax.Array,
batch: Any,
) -> jax.Array:
"""Generate a per-image seed based on the image id or the image values.
Args:
seed: Random seed from which per-image seeds should be derived.
batch: Pytree containing a batch of images (key "image") and optionally
image ids (key "image/id").
Returns:
Array containing per-image ids.
"""
fake_id = None
if "image" in batch:
fake_id = (10**6 * jax.vmap(jnp.mean)(batch["image"])).astype(jnp.int32)
return jax.lax.scan(
lambda k, x: (jax.random.fold_in(k, x), None),
jax.random.PRNGKey(seed),
batch.get("image/id", fake_id),
)[0]
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