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RELEASE.md
import. * Breaking change to `tf.contrib.data.Dataset` APIs that expect a nested structure. Lists are now converted to `tf.Tensor` implicitly. You may need to change uses of lists to tuples in existing code. In addition, dicts are now supported as a nested structure. ## Changes to contrib APIs * Adds tf.contrib.nn.rank_sampled_softmax_loss, a sampled-softmax variant that
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tensorflow/c/eager/gradients.h
// op executed under the tape. A separate map (`tensorflow::eager::OpTape`) // maintains the map from `op_id` to a `OpTapeEntry` which stores the `op_type`, // inputs and outputs and the gradient function These data structures combined // allow us to trace the data dependencies between operations and hence compute // gradients. // // `ZerosLike` is not expected to be called and returns a nullptr. The creation
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tensorflow/BUILD
package_group(name = "types_allowlist") # Packages that use StructuredTensors. # TODO(b/159007891) Remove this package once StructuredTensor is exported. # LINT.IfChange package_group(name = "structured_tensor_allowlist") # LINT.ThenChange(copy.bara.sky) filegroup( name = "intel_binary_blob", data = if_mkl_ml( [ "@local_xla//xla/tsl/mkl:intel_binary_blob", ],
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tensorflow/c/eager/tape.h
#ifndef TENSORFLOW_C_EAGER_TAPE_H_ #define TENSORFLOW_C_EAGER_TAPE_H_ // Language-agnostic gradient tape. Does not perform backpropagation, just // maintains the data structures required to do so. #include <stack> #include <unordered_map> #include <unordered_set> #include <vector> #include "tensorflow/core/config/flag_defs.h" #include "tensorflow/core/config/flags.h"
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tensorflow/c/eager/gradient_checker.cc
// Get theta shape and store in theta_dims. int num_dims = TF_NumDims(theta_tensor); vector<int64_t> theta_dims(num_dims); GetDims(theta_tensor, theta_dims.data()); // Initialize auxilary data structures. vector<float> thetaPlus_data(num_elems); vector<float> thetaMinus_data(num_elems); AbstractTensorHandle* f_outputs[1]; // Numerical Grad Check for (int i = 0; i < num_elems; i++) {
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