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tensorflow/c/c_api_internal.h
// ExtendSessionGraphHelper manually. std::atomic<bool> extend_before_run; }; struct TF_ImportGraphDefOptions { tensorflow::ImportGraphDefOptions opts; // Backing memory for TensorId fields in opts. // TODO(skyewm): it'd be better if ImportGraphDefOptions owned this. std::vector<tensorflow::string> tensor_id_data; }; struct TF_ImportGraphDefResults {
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Sat May 13 00:49:12 GMT 2023 - 7.6K bytes - Viewed (0) -
ci/official/envs/linux_arm64
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_arm64 # Note: this is not set to "--cpu", because that changes the package name # to tensorflow_cpu. These ARM builds are supposed to have the name "tensorflow" # despite lacking Nvidia CUDA support. TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow" TFCI_DOCKER_ENABLE=1 TFCI_DOCKER_IMAGE=gcr.io/tensorflow-sigs/build-arm64:tf-2-16-multi-python TFCI_DOCKER_PULL_ENABLE=1
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tensorflow/c/eager/c_api_remote_test_util.cc
ASSERT_TRUE(remote_arg->HasLocalMirror(nullptr)); } if (remote_func_outputs) { const string backing_device = TFE_TensorHandleBackingDeviceName(retvals[0], status); ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status); EXPECT_EQ(backing_device, task2_name); } auto* retval_task0 = TFE_TensorHandleCopyToDevice(
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SECURITY.md
## Untrusted inputs during training and prediction TensorFlow supports a wide range of input data formats. For example it can process images, audio, videos, and text. There are several modules specialized in taking those formats, modifying them, and/or converting them to intermediate formats that can be processed by TensorFlow. These modifications and conversions are handled by a variety of libraries that
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tensorflow/c/eager/c_api_test_util.h
tensorflow::uint64 send_device_incarnation); // Return a 1-D INT32 tensor containing a single value 1. TFE_TensorHandle* TestAxisTensorHandle(TFE_Context* ctx); // Return an op taking minimum of `input` long `axis` dimension. TFE_Op* MinOp(TFE_Context* ctx, TFE_TensorHandle* input, TFE_TensorHandle* axis); // If there is a device of type `device_type`, returns true
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tensorflow/c/eager/parallel_device/parallel_device_testlib.h
static Variable* Create(TFE_Context* context, TF_DataType type, const int64_t* dims, const int num_dims, const char* device, TF_Status* status); // Dereferences the backing buffer for the variable. Note that since this can // fail (it runs operations), it must be called explicitly and the resulting // `status` checked. void Destroy(TFE_Context* context, TF_Status* status);
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