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tensorflow/c/c_api_test.cc
TF_Graph* graph = TF_NewGraph(); // Make a placeholder operation. TF_Operation* feed = Placeholder(graph, s); ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s); // Make a constant operation with the scalar "2". TF_Operation* two = ScalarConst(2, graph, s); ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s); // Add operation. TF_Operation* add = Add(feed, two, graph, s);
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RELEASE.md
* Added a new `rerandomize_each_iteration` argument for the `tf.data.Dataset.random()` operation, which controls whether the sequence of generated random numbers should be re-randomized every epoch or not (the default behavior). If `seed` is set and `rerandomize_each_iteration=True`, the `random()` operation will produce a different (deterministic) sequence of numbers every epoch.
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tensorflow/c/c_api.cc
namespace { TF_Operation* ToOperation(Node* node) { return static_cast<TF_Operation*>(static_cast<void*>(node)); } string OutputName(const TF_Output& output) { return StrCat(output.oper->node.name(), ":", output.index); } const tensorflow::AttrValue* GetAttrValue(TF_Operation* oper, const char* attr_name,
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CONTRIBUTING.md
just getting started, GitHub has a [how-to](https://help.github.com/articles/using-pull-requests/). TensorFlow team members will be assigned to review your pull requests. Once the pull requests are approved and pass continuous integration checks, a TensorFlow team member will apply `ready to pull` label to your change. This means we are working on getting your pull request submitted to our internal repository. After
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tensorflow/c/BUILD
"//tensorflow/core/common_runtime/eager:attr_builder", "//tensorflow/core/common_runtime/eager:context", "//tensorflow/core/common_runtime/eager:core", "//tensorflow/core/common_runtime/eager:eager_operation", "//tensorflow/core/common_runtime/pluggable_device:pluggable_device_plugin_init", "//tensorflow/core/distributed_runtime/rpc:grpc_server_lib", "//tensorflow/core/platform",
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tensorflow/c/eager/c_api_unified_experimental_graph.cc
TracingOperationPtr operation(CreateOperation()); TF_RETURN_IF_ERROR(operation->Reset("Placeholder", nullptr)); TF_RETURN_IF_ERROR( operation->SetOpName(absl::StrCat("_input_", inputs_.size()).c_str())); TF_RETURN_IF_ERROR(operation->SetAttrType("dtype", dtype)); if (!shape.unknown_rank()) { TF_RETURN_IF_ERROR(operation->SetAttrShape(
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tensorflow/c/eager/BUILD
"@com_google_absl//absl/types:span", ], ) cc_library( name = "immediate_execution_operation", hdrs = ["immediate_execution_operation.h"], visibility = [ "//tensorflow:internal", ], deps = [ ":abstract_operation", ":abstract_tensor_handle", ":immediate_execution_tensor_handle", "//tensorflow/c:tensor_interface",
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tensorflow/c/eager/c_api.cc
status->status = tensorflow::errors::InvalidArgument( "Got a null or uninitialized `op` argument"); return; } tensorflow::EagerOperation* operation = OperationFromInterface(tensorflow::unwrap(const_cast<TFE_Op*>(op))); operation->MutableAttrs()->Set(attr_name, attr_value); } TF_CAPI_EXPORT extern int TFE_OpGetInputLength(TFE_Op* op,
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tensorflow/c/eager/c_api_experimental.cc
#include "tensorflow/core/common_runtime/composite_device.h" #include "tensorflow/core/common_runtime/device.h" #include "tensorflow/core/common_runtime/eager/eager_operation.h" #include "tensorflow/core/distributed_runtime/coordination/coordination_service_error_util.h" #include "tensorflow/core/framework/function.h" #include "tensorflow/core/framework/graph_debug_info.pb.h"
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tensorflow/BUILD
"//learning/serving/contrib/tfrt/mlir/canonical_ops/...", "//learning/serving/experimental/remote_predict/...", "//perftools/accelerators/xprof/convert/...", "//perftools/accelerators/xprof/integration_tests/...", "//smartass/brain/configure/...", "//tensorflow/...", "//tensorflow_decision_forests/...", "//tensorflow_federated/...", "//tensorflow_models/google/recml/...",
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