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tensorflow/c/eager/dlpack_test.cc
EXPECT_EQ(dltensor_out->device.device_type, dltensor_in->device.device_type); EXPECT_EQ(dltensor_out->device.device_id, dltensor_in->device.device_id); EXPECT_EQ(dltensor_out->ndim, dltensor_in->ndim); EXPECT_EQ(dltensor_out->dtype.code, dltensor_in->dtype.code); EXPECT_EQ(dltensor_out->dtype.bits, dltensor_in->dtype.bits); EXPECT_EQ(dltensor_out->dtype.lanes, dltensor_in->dtype.lanes); for (int i = 0; i < dltensor_in->ndim; ++i) {
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Fri Jun 30 03:04:46 GMT 2023 - 4.4K bytes - Viewed (0) -
tensorflow/c/eager/c_api_unified_experimental.cc
TF_Status* s) { unwrap(o)->outputs.push_back(unwrap(tensor)); } void TF_AbstractOpSetOpType(TF_AbstractOp* op, const char* const op_type, TF_Status* s) { tsl::Set_TF_Status_from_Status( s, unwrap(op)->Reset(op_type, /*raw_device_name=*/nullptr)); } void TF_AbstractOpSetOpName(TF_AbstractOp* op, const char* const op_name,
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 09:49:45 GMT 2024 - 9K bytes - Viewed (0) -
tensorflow/c/experimental/next_pluggable_device/tensor_pjrt_buffer_util_test.cc
std::vector<int32_t> data(1, 0); xla::Shape shape = xla::ShapeUtil::MakeShape(xla::S32, {1}); auto buffer = c_api_client->pjrt_c_client()->client->BufferFromHostBuffer( data.data(), shape.element_type(), shape.dimensions(), /*byte_strides=*/std::nullopt, xla::PjRtClient::HostBufferSemantics::kImmutableOnlyDuringCall, nullptr, c_api_client->pjrt_c_client()->client->addressable_devices()[0]);
C++ - Registered: Tue Feb 27 12:39:08 GMT 2024 - Last Modified: Mon Oct 30 19:20:20 GMT 2023 - 7.2K bytes - Viewed (0) -
tensorflow/c/eager/abstract_tensor_handle.cc
shape_string = "<error computing shape>"; } else { shape_string = shape.DebugString(); } return absl::StrCat("TensorHandle(shape=", shape_string, ", dtype=", DataType_Name(DataType()), ", type=", FullType().DebugString(), ")"); } Status AbstractTensorHandle::TensorHandleStatus() const { // Tensor handles in current runtime don't carry error info and this method
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 09:49:45 GMT 2024 - 1.4K bytes - Viewed (0) -
tensorflow/c/eager/custom_device_testutil.cc
auto dtype = TFE_TensorHandleDataType(t->tensor); TFE_CustomDeviceTensorHandleMethods handle_methods; handle_methods.num_dims = &LoggedTensorNumDims; handle_methods.dim = &LoggedTensorDim; handle_methods.deallocator = &LoggedTensorDeallocator; return TFE_NewCustomDeviceTensorHandle(context, logging_device_name.c_str(), dtype, t.release(), handle_methods,
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Wed Mar 03 20:47:31 GMT 2021 - 8.3K bytes - Viewed (0) -
tensorflow/c/eager/gradients_test.cc
absl::Span<AbstractTensorHandle*> outputs) { Tape tape(/*persistent=*/false); tape.Watch(inputs[0]); AbstractTensorHandle* neg_output; TF_RETURN_IF_ERROR(ops::Neg(ctx, inputs[0], &neg_output, "Neg")); tape.RecordOperation(inputs, {neg_output}, nullptr, "Neg"); return tape.ComputeGradient(ctx, /*targets=*/{neg_output},
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Thu Feb 15 09:49:45 GMT 2024 - 7K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/grad_test_helper.cc
absl::Span<AbstractTensorHandle*> outputs) -> Status { Tape tape(/*persistent=*/false); for (size_t i{}; i < inputs.size(); ++i) { tape.Watch(inputs[i]); } std::vector<AbstractTensorHandle*> temp_outputs(1); AbstractContextPtr tape_ctx(new TapeContext(ctx, &tape, grad_registry)); TF_RETURN_IF_ERROR( forward_model(tape_ctx.get(), inputs, absl::MakeSpan(temp_outputs)));
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 5K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/custom_gradient_test.cc
Tape tape(/*persistent=*/false); tape.Watch(inputs[0]); // Watch x. AbstractTensorHandle* exp_output; TF_RETURN_IF_ERROR(ops::Exp(ctx, inputs[0], &exp_output, "Exp")); std::unique_ptr<GradientFunction> gradient_function( new PassThroughGradientFunction); tape.RecordOperation(inputs, {exp_output}, gradient_function.release()); TF_RETURN_IF_ERROR(tape.ComputeGradient(ctx,
C++ - Registered: Tue Mar 26 12:39:09 GMT 2024 - Last Modified: Wed Feb 28 13:53:47 GMT 2024 - 4.8K bytes - Viewed (0) -
tensorflow/c/checkpoint_reader.cc
string key(v2_reader_->key()); (*var_to_shape_map)[key] = TensorShape(entry.shape()); (*var_to_data_type_map)[key] = DataType(entry.dtype()); } // The returned pointers are owned by the caller. return std::make_pair(std::move(var_to_shape_map), std::move(var_to_data_type_map)); } } // namespace checkpoint
C++ - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Fri Aug 25 21:29:12 GMT 2023 - 5.5K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/tape/tape_operation.cc
==============================================================================*/ #include "tensorflow/c/experimental/gradients/tape/tape_operation.h" #include "tensorflow/c/eager/abstract_context.h" #include "tensorflow/c/eager/gradients.h" namespace tensorflow { namespace gradients { TapeOperation::TapeOperation(AbstractOperation* parent_op, Tape* tape, const GradientRegistry& registry) : AbstractOperation(kTape),
C++ - Registered: Tue Feb 27 12:39:08 GMT 2024 - Last Modified: Tue Jun 07 01:53:35 GMT 2022 - 9K bytes - Viewed (1)