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Results 1 - 10 of 23 for itype (0.08 sec)
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tensorflow/compiler/mlir/lite/flatbuffer_export.cc
} if (ftype.isF64()) { return tflite::TensorType_COMPLEX128; } return Status(absl::StatusCode::kInvalidArgument, "Unsupported type"); } else if (auto itype = mlir::dyn_cast<mlir::IntegerType>(type)) { switch (itype.getWidth()) { case 1: return tflite::TensorType_BOOL; case 4: if (itype.isUnsigned()) { return Status(absl::StatusCode::kInvalidArgument,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 21:41:49 UTC 2024 - 164.5K bytes - Viewed (0) -
platforms/documentation/docs/src/snippets/native-binaries/google-test/groovy/libs/googleTest/1.7.0/include/gtest/internal/gtest-type-util.h
T41, T42, T43, T44, T45, T46, T47, T48, T49> type; }; namespace internal { # define GTEST_TEMPLATE_ template <typename T> class // The template "selector" struct TemplateSel<Tmpl> is used to // represent Tmpl, which must be a class template with one type // parameter, as a type. TemplateSel<Tmpl>::Bind<T>::type is defined // as the type Tmpl<T>. This allows us to actually instantiate the
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Mon Nov 27 17:53:42 UTC 2023 - 181.3K bytes - Viewed (0) -
testing/performance/src/templates/native-dependents-resources/googleTest/libs/googleTest/1.7.0/include/gtest/internal/gtest-type-util.h
T41, T42, T43, T44, T45, T46, T47, T48, T49> type; }; namespace internal { # define GTEST_TEMPLATE_ template <typename T> class // The template "selector" struct TemplateSel<Tmpl> is used to // represent Tmpl, which must be a class template with one type // parameter, as a type. TemplateSel<Tmpl>::Bind<T>::type is defined // as the type Tmpl<T>. This allows us to actually instantiate the
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Thu Apr 04 07:21:38 UTC 2024 - 181.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/translate/import_model.cc
VLOG(1) << "[potentially conservative] Op type `" << node.type_string() << "` is stateful but effects not modelled"; } else { // See if any resource type is used. bool resource = false; std::function<bool(mlir::Type)> record_resource; record_resource = [&](mlir::Type type) { type.walk([&](mlir::Type t) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 01 11:17:36 UTC 2024 - 183.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_ops_n_z.cc
dtype == tensorflow::DT_UINT16 || dtype == tensorflow::DT_INT16 || dtype == tensorflow::DT_UINT8 || dtype == tensorflow::DT_INT8 || dtype == tensorflow::DT_HALF || dtype == tensorflow::DT_BFLOAT16 || dtype == tensorflow::DT_FLOAT || dtype == tensorflow::DT_DOUBLE || dtype == tensorflow::DT_COMPLEX64 || dtype == tensorflow::DT_COMPLEX128 || dtype == tensorflow::DT_BOOL) { return {};
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 22:07:10 UTC 2024 - 170.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test.py
bias = array_ops.constant( np.random.uniform(size=[shapes[1][-1]]), dtype=dtypes.float32 ) model = MatmulModel(bias) x = array_ops.constant( np.random.uniform(size=x_shape), dtype=dtypes.float32 ) y = array_ops.constant( np.random.uniform(size=y_shape), dtype=dtypes.float32 ) if use_kernel: model.matmul = model.matmul_with_kernel
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 03:36:50 UTC 2024 - 235.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-composite-functions-tf.mlir
%5 = "tf.Add"(%arg1, %arg2) : (tensor<8x10xf32>, tensor<8x10xf32>) -> tensor<8x10xf32> %6 = "tf.Const"() {_output_shapes = ["tfshape$"], device = "/device:CPU:0", dtype = f32, value = dense<1.000000e+00> : tensor<f32>} : () -> tensor<f32> func.return %5, %4, %5, %5, %6 : tensor<8x10xf32>, tensor<?x8x10xf32>, tensor<8x10xf32>, tensor<8x10xf32>, tensor<f32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 122.1K bytes - Viewed (0) -
tensorflow/c/c_api.cc
metadata.type = TF_ATTR_INT; } else if (typestr == "list(float)") { metadata.type = TF_ATTR_FLOAT; } else if (typestr == "list(bool)") { metadata.type = TF_ATTR_BOOL; } else if (typestr == "list(type)") { metadata.type = TF_ATTR_TYPE; } else if (typestr == "list(shape)") { metadata.type = TF_ATTR_SHAPE;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 15 03:35:10 UTC 2024 - 102.3K bytes - Viewed (0) -
tensorflow/compiler/jit/extract_outside_compilation_pass.cc
for (auto* n : arg_nodes) { int index; TF_RETURN_IF_ERROR(GetNodeAttr(n->attrs(), "index", &index)); DataType dtype; TF_RETURN_IF_ERROR(GetNodeAttr(n->attrs(), "T", &dtype)); (*recv_at_host_dtypes)[index] = dtype; } for (int i = 0, end = recv_at_host_dtypes->size(); i < end; i++) { if ((*recv_at_host_dtypes)[i] == DT_INVALID) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 12 06:33:33 UTC 2024 - 104.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/legalize-tf.mlir
%1 = "tf.Const"() {device = "", dtype = f32, value = dense<0.000000e+00>: tensor<16x28xf32>} : () -> tensor<16x28xf32> %2 = "tf.Const"() {device = "", dtype = f32, value = dense<0.000000e+00>: tensor<16x16xf32>} : () -> tensor<16x16xf32> %3 = "tf.Const"() {device = "", dtype = f32, value = dense<0.000000e+00>: tensor<16xf32>} : () -> tensor<16xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 05 01:54:33 UTC 2024 - 153.4K bytes - Viewed (0)