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tensorflow/c/BUILD
":env", ":logging", ":tf_status", ":tf_tensor", "//tensorflow/c/experimental/filesystem:modular_filesystem", "//tensorflow/cc:grad_ops", "//tensorflow/cc:gradients", "//tensorflow/cc:ops", "//tensorflow/cc:scope_internal", "//tensorflow/cc:while_loop",
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RELEASE.md
* Infer `tf.contrib.distributions.RelaxedOneHotCategorical` `dtype` from arguments. * Make `tf.contrib.distributions` quadrature family parameterized by `quadrature_grid_and_prob` vs `quadrature_degree`. * `auto_correlation` added to `tf.contrib.distributions` * Add `tf.contrib.bayesflow.layers`, a collection of probabilistic (neural) layers.
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tensorflow/c/eager/BUILD
"//tensorflow/c:c_api", "//tensorflow/c:c_test_util", "//tensorflow/c:tf_status_helper", "//tensorflow/c/experimental/gradients:array_grad", "//tensorflow/c/experimental/gradients:math_grad", "//tensorflow/c/experimental/gradients:not_differentiable", "//tensorflow/c/experimental/gradients/tape:tape_context", "//tensorflow/c/experimental/ops",
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tensorflow/c/experimental/gradients/BUILD
], ) cc_library( name = "gradients", hdrs = [ "array_grad.h", "math_grad.h", "nn_grad.h", "not_differentiable.h", ], visibility = [ "//tensorflow:internal", ], deps = [ ":array_grad", ":math_grad", ":nn_grad", ":not_differentiable", "//tensorflow/c/eager:abstract_context",
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