0e1f3de50a
`KerasTensor`s are an alternative representation for Keras `Inputs`
and for intermediate outputs of layers during Functional API construction of
models. They are a lightweight data structure comprised of only the
`tf.TypeSpec` of the Tensor that will be consumed/produced in the
corresponding position of the model.
They implement just small subset of `tf.Tensor`'s attributes and
methods, and also overload
the same operators as `tf.Tensor` and automatically turn them into
Keras layers in the model.
`KerasTensor`s are still internal-only and are a work in progress, but they
have several advantages over using a graph `tf.Tensor` to represent
symbolic values in functional models.
- Unlike symbolic tensors, they do not need to refer to a graph. This means
Keras does not need to maintain a never-deleted global background graph
containing all layers ever called during functional model construction when
constructing Functional Models with KerasTensors. These memory savings
can be significant.
- Triggering Keras functional model construction is simpler
when it just has to check whether something is a KerasTensor, rather
than trying to infer if a tensor was meant to be a symbolic keras
representation or just a value produced during function tracing. This means we can add support for cases where values in nest.flatten(*args, **kwargs) are a completely arbitrary mix of KerasTensors and objects that are not KerasTensors, as long as any value is a KerasTensor.
- Autolambda layers (converting tf ops on symbolic Keras tensors to lambda
Keras layers in the model) use TF's internal dispatching mechanism, instead
of trying to manually walk a graph and extract nodes from it.
The dispatching mechanism is simpler, works more reliably, and is less
likely to run into issues with composite tensors or strange tf ops/nodes.
(And when it fails, it's by design: because dispatch is explicitly not
supported on the op & it's more obvious that dispatch doesn't support the
setting).
- Because they support arbitrary typespecs, models/layers that use
KerasTensors are generally more friendly to composite tensors of different
types than using symbolic graph tensors (which must have a TensorSpec and
can't have arbitrary typespecs)
To experiment with using KerasTensors instead of symbolic graph `tf.Tensors`,
import keras_tensor directly and call `keras_tensor.enable_keras_tensors()`
PiperOrigin-RevId: 315009281
Change-Id: I6765f3a44da43f965ec261b6b193df26598cffae
634 lines
17 KiB
Python
Executable File
634 lines
17 KiB
Python
Executable File
# Description:
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# Contains the Keras API (internal TensorFlow version).
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load("//tensorflow:tensorflow.bzl", "tf_py_test")
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package(
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default_visibility = ["//visibility:public"],
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licenses = ["notice"], # Apache 2.0
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)
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exports_files(["LICENSE"])
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py_library(
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name = "keras",
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srcs = [
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"__init__.py",
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"estimator/__init__.py",
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"keras_parameterized.py",
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],
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srcs_version = "PY2AND3",
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deps = [
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":backend",
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":engine",
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# TODO(scottzhu): Stop exporting the test_utils after removing all
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# callers that using it.
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":testing_utils",
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"//tensorflow/python:training",
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"//tensorflow/python/eager:monitoring",
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"//tensorflow/python/keras/applications",
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"//tensorflow/python/keras/datasets",
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"//tensorflow/python/keras/feature_column",
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"//tensorflow/python/keras/layers",
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"//tensorflow/python/keras/mixed_precision/experimental:mixed_precision_experimental",
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"//tensorflow/python/keras/optimizer_v2",
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"//tensorflow/python/keras/premade",
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"//tensorflow/python/keras/preprocessing",
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"//tensorflow/python/keras/saving",
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"//tensorflow/python/keras/utils",
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"//tensorflow/python/keras/wrappers",
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"//tensorflow/python/saved_model",
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],
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)
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py_library(
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name = "backend",
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srcs = ["backend.py"],
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srcs_version = "PY2AND3",
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deps = [
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":backend_config",
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"//tensorflow/core:protos_all_py",
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"//tensorflow/python:array_ops",
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"//tensorflow/python:check_ops",
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"//tensorflow/python:client",
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"//tensorflow/python:clip_ops",
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"//tensorflow/python:composite_tensor_utils",
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"//tensorflow/python:constant_op",
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"//tensorflow/python:control_flow_ops",
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"//tensorflow/python:control_flow_util",
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"//tensorflow/python:ctc_ops",
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"//tensorflow/python:dtypes",
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"//tensorflow/python:framework",
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"//tensorflow/python:framework_ops",
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"//tensorflow/python:functional_ops",
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"//tensorflow/python:gradients",
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"//tensorflow/python:image_ops",
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"//tensorflow/python:init_ops",
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"//tensorflow/python:init_ops_v2",
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"//tensorflow/python:logging_ops",
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"//tensorflow/python:map_fn",
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"//tensorflow/python:math_ops",
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"//tensorflow/python:metrics",
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"//tensorflow/python:nn",
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"//tensorflow/python:platform",
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"//tensorflow/python:random_ops",
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"//tensorflow/python:session",
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"//tensorflow/python:sparse_ops",
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"//tensorflow/python:sparse_tensor",
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"//tensorflow/python:state_ops",
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"//tensorflow/python:summary",
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"//tensorflow/python:tensor_array_grad",
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"//tensorflow/python:tensor_array_ops",
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"//tensorflow/python:tensor_shape",
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"//tensorflow/python:training_lib",
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"//tensorflow/python:util",
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"//tensorflow/python:variables",
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"//tensorflow/python/distribute:distribute_coordinator",
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"//tensorflow/python/distribute:distribute_lib",
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"//tensorflow/python/distribute:multi_worker_util",
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"//tensorflow/python/keras/engine:keras_tensor",
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],
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)
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py_library(
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name = "backend_config",
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srcs = ["backend_config.py"],
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srcs_version = "PY2AND3",
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deps = ["//tensorflow/python:util"],
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)
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# TODO(scottzhu): Cleanup this target and point all the user to keras/engine.
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py_library(
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name = "engine",
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srcs = [
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":metrics",
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":models",
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],
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srcs_version = "PY2AND3",
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deps = [
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"//tensorflow/python/keras/engine",
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],
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)
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py_library(
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name = "activations",
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srcs = [
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"activations.py",
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],
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srcs_version = "PY2AND3",
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deps = [
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":backend",
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"//tensorflow/python/keras/utils:engine_utils",
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],
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)
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# TODO(scottzhu): Cleanup this target and point all the user to keras/engine.
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py_library(
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name = "base_layer",
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srcs = [],
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srcs_version = "PY2AND3",
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deps = [
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"//tensorflow/python/keras/engine:base_layer",
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],
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)
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py_library(
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name = "callbacks",
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srcs = [
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"callbacks.py",
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],
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srcs_version = "PY2AND3",
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deps = [
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":backend",
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"//tensorflow/python/distribute:distributed_file_utils",
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"//tensorflow/python/keras/distribute:worker_training_state",
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"//tensorflow/python/keras/protobuf:projector_config_proto_py",
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"//tensorflow/python/keras/utils:engine_utils",
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"//tensorflow/python/keras/utils:mode_keys",
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"//tensorflow/python/profiler:profiler_v2",
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"//tensorflow/tools/docs:doc_controls",
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],
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)
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py_library(
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name = "combinations",
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srcs = [
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"combinations.py",
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],
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deps = [
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":testing_utils",
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"//tensorflow/python:framework_combinations",
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"//tensorflow/python:framework_test_combinations_lib",
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"//tensorflow/python:tf2",
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],
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)
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py_library(
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name = "callbacks_v1",
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srcs = [
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"callbacks_v1.py",
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],
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srcs_version = "PY2AND3",
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deps = [
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":backend",
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"//tensorflow/python/keras/utils:engine_utils",
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"//tensorflow/python/profiler:profiler_v2",
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],
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)
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py_library(
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name = "constraints",
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srcs = [
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"constraints.py",
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],
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srcs_version = "PY2AND3",
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deps = [
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":backend",
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"//tensorflow/python/keras/utils:engine_utils",
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],
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)
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py_library(
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name = "initializers",
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srcs = [
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"initializers/__init__.py",
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"initializers/initializers_v1.py",
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"initializers/initializers_v2.py",
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],
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srcs_version = "PY2AND3",
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deps = [
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":backend",
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"//tensorflow/python:init_ops_v2",
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"//tensorflow/python/keras/utils:engine_utils",
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],
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)
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py_library(
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name = "losses",
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srcs = [
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"losses.py",
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],
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srcs_version = "PY2AND3",
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deps = [
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":backend",
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"//tensorflow/python/keras/utils:engine_utils",
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],
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)
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py_library(
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name = "metrics",
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srcs = [
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"metrics.py",
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],
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srcs_version = "PY2AND3",
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deps = [
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":backend",
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":losses",
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"//tensorflow/python:array_ops",
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"//tensorflow/python:check_ops",
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"//tensorflow/python:confusion_matrix",
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"//tensorflow/python:constant_op",
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"//tensorflow/python:control_flow_ops",
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"//tensorflow/python:dtypes",
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"//tensorflow/python:framework_ops",
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"//tensorflow/python:init_ops",
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"//tensorflow/python:math_ops",
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"//tensorflow/python:nn",
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"//tensorflow/python:tensor_shape",
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"//tensorflow/python:util",
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"//tensorflow/python:variables",
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"//tensorflow/python:weights_broadcast_ops",
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"//tensorflow/python/distribute:distribute_lib",
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"//tensorflow/python/eager:context",
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"//tensorflow/python/eager:def_function",
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"//tensorflow/python/keras/distribute",
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"//tensorflow/python/keras/engine:base_layer",
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"//tensorflow/python/keras/engine:base_layer_utils",
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"//tensorflow/python/keras/utils:generic_utils",
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"//tensorflow/python/keras/utils:metrics_utils",
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"//tensorflow/python/keras/utils:tf_utils",
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"//tensorflow/python/ops/losses",
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"//tensorflow/tools/docs:doc_controls",
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"//third_party/py/numpy",
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"@six_archive//:six",
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],
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)
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py_library(
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name = "models",
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srcs = [
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"models.py",
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],
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srcs_version = "PY2AND3",
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deps = [
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":backend",
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":metrics",
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":optimizers",
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"//tensorflow/python:platform",
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"//tensorflow/python:util",
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"//tensorflow/python/keras/engine",
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"//tensorflow/python/keras/engine:base_layer",
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"//tensorflow/python/keras/saving",
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"//tensorflow/python/keras/utils:generic_utils",
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"//tensorflow/python/keras/utils:version_utils",
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],
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)
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py_library(
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name = "optimizers",
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srcs = [
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"optimizers.py",
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],
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srcs_version = "PY2AND3",
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deps = [
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":backend",
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"//tensorflow/python/keras/optimizer_v2",
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"//tensorflow/python/keras/utils:engine_utils",
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],
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)
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py_library(
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name = "regularizers",
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srcs = [
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"regularizers.py",
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],
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srcs_version = "PY2AND3",
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deps = [
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":backend",
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"//tensorflow/python/keras/utils:engine_utils",
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],
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)
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py_library(
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name = "testing_utils",
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srcs = [
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"testing_utils.py",
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],
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deps = [
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":backend",
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":models",
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"//tensorflow/python:framework_test_lib",
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"//tensorflow/python:tensor_shape",
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"//tensorflow/python:tensor_spec",
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"//tensorflow/python:tf2",
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"//tensorflow/python:util",
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"//tensorflow/python/eager:context",
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"//tensorflow/python/keras/engine:base_layer_utils",
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"//tensorflow/python/keras/layers",
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"//tensorflow/python/keras/optimizer_v2",
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"//third_party/py/numpy",
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],
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)
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tf_py_test(
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name = "activations_test",
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size = "small",
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srcs = ["activations_test.py"],
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python_version = "PY3",
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deps = [
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":activations",
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":backend",
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":combinations",
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"//tensorflow/python:client_testlib",
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"//tensorflow/python:nn_ops",
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"//tensorflow/python/keras/layers",
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"//tensorflow/python/keras/layers:advanced_activations",
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"//tensorflow/python/keras/layers:core",
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"//third_party/py/numpy",
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"@absl_py//absl/testing:parameterized",
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],
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)
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tf_py_test(
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name = "combinations_test",
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size = "small",
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srcs = ["combinations_test.py"],
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python_version = "PY3",
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deps = [
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":combinations",
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":testing_utils",
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"//tensorflow/python:client_testlib",
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"//tensorflow/python:extra_py_tests_deps",
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"//tensorflow/python:tf2",
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"//tensorflow/python/eager:context",
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"@absl_py//absl/testing:parameterized",
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],
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)
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tf_py_test(
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name = "constraints_test",
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size = "small",
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srcs = ["constraints_test.py"],
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python_version = "PY3",
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deps = [
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":backend",
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":combinations",
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":constraints",
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"//tensorflow/python:client_testlib",
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"//third_party/py/numpy",
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],
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)
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tf_py_test(
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name = "initializers_test",
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size = "small",
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srcs = ["initializers_test.py"],
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python_version = "PY3",
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deps = [
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":backend",
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":combinations",
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":initializers",
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":models",
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"//tensorflow/python:array_ops",
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"//tensorflow/python:client_testlib",
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"//tensorflow/python:framework_test_lib",
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"//tensorflow/python:init_ops",
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"//tensorflow/python:tf2",
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"//tensorflow/python/keras/engine",
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"//third_party/py/numpy",
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],
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)
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tf_py_test(
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name = "regularizers_test",
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size = "medium",
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srcs = ["regularizers_test.py"],
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python_version = "PY3",
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deps = [
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":keras",
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"//tensorflow/python:client_testlib",
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"@absl_py//absl/testing:parameterized",
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],
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)
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tf_py_test(
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name = "optimizers_test",
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size = "medium",
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srcs = ["optimizers_test.py"],
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python_version = "PY3",
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shard_count = 8,
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tags = ["notsan"],
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deps = [
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":keras",
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"//tensorflow/python:client_testlib",
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"//tensorflow/python:training",
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"//third_party/py/numpy",
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"@absl_py//absl/testing:parameterized",
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],
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)
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tf_py_test(
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name = "losses_test",
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size = "small",
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srcs = ["losses_test.py"],
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python_version = "PY3",
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deps = [
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":backend",
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":combinations",
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":losses",
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"//tensorflow/python:client_testlib",
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"//tensorflow/python:constant_op",
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"//tensorflow/python:dtypes",
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"//tensorflow/python:errors",
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"//tensorflow/python:framework_ops",
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"//tensorflow/python:framework_test_lib",
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"//tensorflow/python/keras/utils:engine_utils",
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"//third_party/py/numpy",
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],
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)
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tf_py_test(
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name = "metrics_functional_test",
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size = "small",
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srcs = ["metrics_functional_test.py"],
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python_version = "PY3",
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deps = [
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":keras",
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"//tensorflow/python:client_testlib",
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"//third_party/py/numpy",
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],
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)
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tf_py_test(
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name = "metrics_test",
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size = "medium",
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srcs = ["metrics_test.py"],
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python_version = "PY3",
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shard_count = 4,
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deps = [
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":combinations",
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":keras",
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":metrics",
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":testing_utils",
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"//tensorflow/python:array_ops",
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"//tensorflow/python:client_testlib",
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"//tensorflow/python:constant_op",
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"//tensorflow/python:dtypes",
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"//tensorflow/python:errors",
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"//tensorflow/python:framework_ops",
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"//tensorflow/python:framework_test_lib",
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"//tensorflow/python:math_ops",
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"//tensorflow/python:variables",
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"//tensorflow/python:weights_broadcast_ops",
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"//tensorflow/python/eager:context",
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"//tensorflow/python/eager:def_function",
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"//tensorflow/python/eager:function",
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"//tensorflow/python/keras/layers",
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"//tensorflow/python/ops/ragged:ragged_factory_ops",
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"//tensorflow/python/training/tracking:util",
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"//third_party/py/numpy",
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],
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)
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tf_py_test(
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name = "metrics_confusion_matrix_test",
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size = "medium",
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srcs = ["metrics_confusion_matrix_test.py"],
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python_version = "PY3",
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shard_count = 4,
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deps = [
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":combinations",
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":metrics",
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":models",
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"//tensorflow/python:client_testlib",
|
|
"//tensorflow/python:constant_op",
|
|
"//tensorflow/python:dtypes",
|
|
"//tensorflow/python:math_ops",
|
|
"//tensorflow/python:random_ops",
|
|
"//tensorflow/python:variables",
|
|
"//tensorflow/python/keras/layers",
|
|
"//tensorflow/python/keras/utils:metrics_utils",
|
|
"//third_party/py/numpy",
|
|
"@absl_py//absl/testing:parameterized",
|
|
],
|
|
)
|
|
|
|
tf_py_test(
|
|
name = "metrics_correctness_test",
|
|
size = "medium",
|
|
srcs = ["metrics_correctness_test.py"],
|
|
python_version = "PY3",
|
|
shard_count = 4,
|
|
deps = [
|
|
":keras",
|
|
"//tensorflow/python:client_testlib",
|
|
"//third_party/py/numpy",
|
|
"@absl_py//absl/testing:parameterized",
|
|
],
|
|
)
|
|
|
|
tf_py_test(
|
|
name = "callbacks_test",
|
|
size = "medium",
|
|
srcs = ["callbacks_test.py"],
|
|
python_version = "PY3",
|
|
shard_count = 4,
|
|
tags = [
|
|
"no_oss",
|
|
"notsan",
|
|
],
|
|
deps = [
|
|
":keras",
|
|
"//third_party/py/numpy",
|
|
"@absl_py//absl/testing:parameterized",
|
|
"@six_archive//:six",
|
|
],
|
|
)
|
|
|
|
tf_py_test(
|
|
name = "callbacks_v1_test",
|
|
size = "medium",
|
|
srcs = ["callbacks_v1_test.py"],
|
|
python_version = "PY3",
|
|
tags = ["notsan"],
|
|
deps = [
|
|
":callbacks",
|
|
":callbacks_v1",
|
|
":combinations",
|
|
":testing_utils",
|
|
"//tensorflow/python:client_testlib",
|
|
"//tensorflow/python:framework_ops",
|
|
"//tensorflow/python:training_lib",
|
|
"//tensorflow/python/keras/engine",
|
|
"//tensorflow/python/keras/layers",
|
|
"//tensorflow/python/keras/utils:np_utils",
|
|
"//third_party/py/numpy",
|
|
"@absl_py//absl/testing:parameterized",
|
|
],
|
|
)
|
|
|
|
tf_py_test(
|
|
name = "models_test",
|
|
size = "medium",
|
|
srcs = ["models_test.py"],
|
|
python_version = "PY3",
|
|
shard_count = 8,
|
|
tags = [
|
|
"no_rocm",
|
|
"notsan", # b/67509773
|
|
],
|
|
deps = [
|
|
":keras",
|
|
"//tensorflow/python:client_testlib",
|
|
"//tensorflow/python:training",
|
|
"//third_party/py/numpy",
|
|
"@absl_py//absl/testing:parameterized",
|
|
],
|
|
)
|
|
|
|
tf_py_test(
|
|
name = "backend_test",
|
|
size = "medium",
|
|
srcs = ["backend_test.py"],
|
|
python_version = "PY3",
|
|
shard_count = 4,
|
|
deps = [
|
|
":backend",
|
|
":combinations",
|
|
":engine",
|
|
"//tensorflow/core:protos_all_py",
|
|
"//tensorflow/python:array_ops",
|
|
"//tensorflow/python:client_testlib",
|
|
"//tensorflow/python:config",
|
|
"//tensorflow/python:errors",
|
|
"//tensorflow/python:extra_py_tests_deps",
|
|
"//tensorflow/python:framework_ops",
|
|
"//tensorflow/python:framework_test_lib",
|
|
"//tensorflow/python:nn",
|
|
"//tensorflow/python:sparse_tensor",
|
|
"//tensorflow/python:util",
|
|
"//tensorflow/python:variables",
|
|
"//tensorflow/python/eager:context",
|
|
"//tensorflow/python/eager:def_function",
|
|
"//third_party/py/numpy",
|
|
"@absl_py//absl/testing:parameterized",
|
|
],
|
|
)
|
|
|
|
tf_py_test(
|
|
name = "backend_config_test",
|
|
size = "medium",
|
|
srcs = ["backend_config_test.py"],
|
|
python_version = "PY3",
|
|
deps = [
|
|
":backend",
|
|
":backend_config",
|
|
":combinations",
|
|
"//tensorflow/python:client_testlib",
|
|
],
|
|
)
|
|
|
|
tf_py_test(
|
|
name = "keras_parameterized_test",
|
|
size = "small",
|
|
srcs = ["keras_parameterized_test.py"],
|
|
python_version = "PY3",
|
|
tags = ["notsan"],
|
|
deps = [
|
|
":keras",
|
|
"//tensorflow/python:client_testlib",
|
|
"//third_party/py/numpy",
|
|
"@absl_py//absl/testing:parameterized",
|
|
],
|
|
)
|