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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) -
platforms/core-configuration/declarative-dsl-core/src/main/kotlin/org/gradle/internal/declarativedsl/schemaBuilder/schemaBuildingUtils.kt
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Tue May 14 10:08:01 UTC 2024 - 2.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/fold_broadcast_pass.cc
LogicalResult ConstantFoldMul(mhlo::MulOp op, PatternRewriter &rewriter) { ShapedType type = mlir::dyn_cast<ShapedType>(op.getType()); Type etype = type.getElementType(); Attribute result = {}; if (mlir::isa<FloatType>(etype)) { result = BinaryFolder<mhlo::MulOp, FloatType, APFloat, std::multiplies<APFloat>>( &op); } else if (mlir::isa<IntegerType>(etype)) { result =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 10.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/tf_to_corert/fallback.mlir
%dense_default_0 = "tf.Const"() {device = "/device:CPU:0", dtype = f32, value = dense<[]> : tensor<0xf32>} : () -> tensor<0xf32> %dense_default_1 = "tf.Const"() {device = "/device:CPU:0", dtype = f32, value = dense<[]> : tensor<0xf32>} : () -> tensor<0xf32> %dense_keys = "tf.Const"() {device = "/device:CPU:0", dtype = !tf_type.string, value = dense<""> : tensor<2x!tf_type.string>} : () -> tensor<2x!tf_type.string>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 00:18:59 UTC 2024 - 9.1K bytes - Viewed (0) -
src/runtime/export_debug_test.go
if tid == 0 { return nil, plainError("missing tid") } f := efaceOf(&fn) if f._type == nil || f._type.Kind_&abi.KindMask != abi.Func { return nil, plainError("fn must be a function") } fv := (*funcval)(f.data) a := efaceOf(&stackArgs) if a._type != nil && a._type.Kind_&abi.KindMask != abi.Pointer { return nil, plainError("args must be a pointer or nil") } argp := a.data
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Fri May 17 15:41:45 UTC 2024 - 5.1K bytes - Viewed (0) -
tensorflow/cc/experimental/libtf/impl/tensor_spec_test.cc
tensorflow::PartialTensorShape unknown_shape; TensorSpec ts1; ts1.shape = unknown_shape; ts1.dtype = tensorflow::DT_FLOAT; TensorSpec ts2; ts2.shape = tensorflow::PartialTensorShape({2}); ts2.dtype = tensorflow::DT_FLOAT; TensorSpec ts3; ts3.shape = tensorflow::PartialTensorShape({1, 2}); ts3.dtype = tensorflow::DT_FLOAT; EXPECT_TRUE(absl::VerifyTypeImplementsAbslHashCorrectly({ts1, ts2, ts3})); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 18 09:47:46 UTC 2024 - 1.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/compose-uniform-quantized-type.mlir
// RUN: odml-to-stablehlo-opt --compose-uniform-quantized-type \ // RUN: --split-input-file --verify-diagnostics %s | FileCheck %s module { // CHECK-LABEL: quantized_conv_op // CHECK-SAME: %[[ARG:.*]]: tensor<1x3x3x4xf32> func.func @quantized_conv_op(%arg0: tensor<1x3x3x4xf32>) -> tensor<1x3x3x4xf32> { %1 = stablehlo.constant dense<1.000000e+03> : tensor<1x1x1x1xf32> // Input inverse scale.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 37K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/end2end/fake_quant_per_channel_4bit.pbtxt
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 18.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/end2end/unroll_batch_matmul_disabled.pbtxt
node { name: "Placeholder" op: "Placeholder" attr { key: "dtype" value { type: DT_FLOAT } } attr { key: "shape" value { shape { dim { size: 2 } dim { size: 5 } dim {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 1.5K bytes - Viewed (0) -
testing/performance/src/templates/native-dependents-resources/googleTest/libs/googleTest/1.7.0/include/gtest/internal/gtest-type-util.h.pump
typedef internal::Types$i<$for j, [[T$j]]> 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 - 9.1K bytes - Viewed (0)