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tensorflow/api_template.__init__.py
""" # pylint: disable=g-bad-import-order,protected-access,g-import-not-at-top import distutils as _distutils import importlib import inspect as _inspect import os as _os import site as _site import sys as _sys # Do not remove this line; See https://github.com/tensorflow/tensorflow/issues/42596
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tensorflow/api_template_v1.__init__.py
# ============================================================================== """Bring in all of the public TensorFlow interface into this module.""" import distutils as _distutils import importlib import inspect as _inspect import os as _os import site as _site import sys as _sys # pylint: disable=g-bad-import-order,protected-access,g-import-not-at-top from tensorflow.python import pywrap_tensorflow # pylint: disable=unused-import
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ci/official/utilities/setup_docker.sh
docker push "$TFCI_DOCKER_IMAGE" fi fi # Keep the existing "tf" container if it's already present. # The container is not cleaned up automatically! Remove it with: # docker rm tf if ! docker container inspect tf >/dev/null 2>&1 ; then # Pass all existing TFCI_ variables into the Docker container env_file=$(mktemp) env | grep ^TFCI_ > "$env_file" docker run $TFCI_DOCKER_ARGS --name tf -w "$TFCI_GIT_DIR" -itd --rm \
Shell Script - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Fri Jan 26 15:27:59 GMT 2024 - 1.8K bytes - Viewed (0) -
CONTRIBUTING.md
### Typical Pull Request Workflow - **1. New PR** - As a contributor, you submit a New PR on GitHub. - We inspect every incoming PR and add certain labels to the PR such as `size:`, `comp:` etc. At this stage we check if the PR is valid and meets certain quality requirements. For example, we check if the CLA is signed, PR has
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tensorflow/c/eager/c_api.h
// Fetches the current number of inputs attached to `op`. // // Does not use the operation's definition to determine how many inputs should // be attached. It is intended for use with TFE_OpGetFlatInput to inspect an // already-finalized operation. // // Note that TFE_OpGetFlatInputCount and TFE_OpGetFlatInput operate on a flat // sequence of inputs, unlike TFE_OpGetInputLength (for getting the length of a
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tensorflow/c/eager/c_api_experimental.h
// APIs for generically dealing with op attributes (e.g. when forwarding them // through custom device implementations). // // TODO(allenl): Currently these are black boxes, but we should have some way to // inspect values. This would let people e.g. copy over most attributes and then // modify some based on their values. // A reference to an op's name -> attribute mapping typedef struct TFE_OpAttrs TFE_OpAttrs;
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RELEASE.md
* Make the Bigtable client connection pool configurable & increase the default # of connections for performance. * Added derivative of `tf.random_gamma` with respect to the alpha parameter. * Added derivative of `tf.igamma(a, x)` and `tf.igammac(a, x)` with respect to a. * Modified Bessel functions of order zero and one. * Add FillTriangular Bijector to create triangular matrices.
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tensorflow/c/eager/gradients.h
void DeleteTrace(const AbstractTensorHandle*); // Consumes the internal state of the tape (so cannot be called more than // once unless the tape is persistent) and produces the gradient of the target // tensors with respect to the source tensors. The output gradients are used // if not empty and not null. The result is populated with one tensor per // target element. Status ComputeGradient(
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tensorflow/c/eager/tape.h
void DeleteTrace(int64_t tensor_id); // Consumes the internal state of the tape (so cannot be called more than // once) and produces the gradient of the target tensors with respect to the // source tensors. The output gradients are used if not empty and not // null. The result is populated with one tensor per target element. // When running backward functions, builds zeros-like tensors for
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tensorflow/c/eager/parallel_device/parallel_device_lib.h
// ParallelDevice. class ParallelTensor { public: // Construct a ParallelTensor from TensorHandles placed on the component // devices of a ParallelDevice. If called, ParallelTensor::Shape inspects // `components` to determine a shape. static std::unique_ptr<ParallelTensor> FromTensorHandles( const ParallelDevice& parallel_device, std::vector<TensorHandlePtr> components, TF_Status* status);
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