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tensorflow/compiler/aot/aot_only_var_handle_op.cc
.Attr("shared_name: string = ''") .Attr("debug_name: string = ''") .Attr("dtype: type") .Attr("shape: shape") .Output("resource: resource") .SetIsStateful() .SetShapeFn([](shape_inference::InferenceContext* c) { c->set_output(0, c->Scalar()); DataType t; TF_RETURN_IF_ERROR(c->GetAttr("dtype", &t)); PartialTensorShape p; TF_RETURN_IF_ERROR(c->GetAttr("shape", &p));
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 28 09:57:04 UTC 2024 - 3K 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
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 15 09:49:45 UTC 2024 - 1.4K bytes - Viewed (0) -
tensorflow/c/eager/immediate_execution_tensor_handle.cc
const char* device_name = DeviceName(&s); if (!s.ok()) { device_name = "<error fetching device name>"; } return absl::StrCat("TensorHandle(", value_string, ", shape=", shape_string, ", dtype=", DataType_Name(DataType()), ", device=\"", device_name, "\")"); } Status ImmediateExecutionTensorHandle::SummarizeValue( std::string& summary) const { Status status;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 15 09:49:45 UTC 2024 - 2.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/utils/tf_type_utils.cc
namespace mlir::quant::tensorflow { bool IsTFQintType(const Type type) { return mlir::isa<TF::Qint8Type, TF::Qint16Type, TF::Qint32Type, TF::Quint8Type, TF::Quint16Type>(type); } Type GetIntTypeFromTFQint(const Type type) { return TypeSwitch<Type, Type>(type) .Case<TF::Qint8Type>( [&type](Type) { return IntegerType::get(type.getContext(), 8); }) .Case<TF::Qint16Type>(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 4.1K bytes - Viewed (0) -
tensorflow/cc/experimental/libtf/function.cc
} Status VerifySupportedSignature(TaggedValue signature) { if (signature.type() == TaggedValue::Type::TENSOR_SPEC) { return ::tensorflow::OkStatus(); } if (signature.type() == TaggedValue::Type::TUPLE) { for (const auto& t : signature.tuple()) { if (t.type() != TaggedValue::Type::TENSOR_SPEC) { break; } } return ::tensorflow::OkStatus(); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Mar 04 19:49:06 UTC 2024 - 9.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/bridge/legalize_tf_quant_test.cc
// Set up an arg per arg_shape with the specified type. for (int i = 0; i < arg_shapes.size(); ++i) { auto metadata_arg = metadata_proto.add_args(); metadata_arg->set_kind( tensorflow::tpu::TPUCompileMetadataProto::Arg::PARAMETER); metadata_arg->set_dtype(dtype); } // Set up one dummy retval. metadata_proto.add_retvals();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 29 18:43:55 UTC 2024 - 7.2K bytes - Viewed (0) -
tensorflow/compiler/jit/xla_tensor.cc
} else { return se::DeviceMemoryBase(const_cast<char*>(tensor.tensor_data().data()), tensor.tensor_data().size()); } } Status XlaTensor::AllocateShapedBuffer(DataType dtype, const xla::Shape& on_device_shape, xla::LocalClient* client, int device_ordinal) { xla::Shape on_host_shape =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 22 08:47:20 UTC 2024 - 4.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/api/v1/compile_mlir_util_test.cc
auto build_result = BuildHloFromGraph(*graph, /*use_output_shapes=*/true); ASSERT_FALSE(build_result.ok()); EXPECT_THAT(build_result.message(), HasSubstr("op operand type 'tensor<2x3x4x5xi32>' and result type " "'tensor<1xi32>' are cast incompatible")); } } // namespace
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Mar 25 19:54:38 UTC 2024 - 9.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/lift_variables.cc
// If the arg type already matches the global_tensor type, we don't need // to do anything. if (!underlying_type.empty() && underlying_type[0] == global_tensor.getType()) { assert(underlying_type.size() == 1); continue; } // Otherwise, set this argument's type to the global_tensor's type. auto new_arg_type = mlir::RankedTensorType::get(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 23 09:05:47 UTC 2024 - 7.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/initialize_variables_in_session_init.cc
for (auto var_and_tensor : llvm::zip(var_ops, resource_tensors_or.value())) { auto& var_op = std::get<0>(var_and_tensor); auto& resource_tensor = std::get<1>(var_and_tensor); if (resource_tensor.dtype() != tensorflow::DT_RESOURCE) { InitializeVariable(var_op, &resource_tensor, session_init_func, builder); continue; } auto handle = resource_tensor.scalar<tensorflow::ResourceHandle>()();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 23 09:05:47 UTC 2024 - 7K bytes - Viewed (0)