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Results 41 - 50 of 63 for _output_shapes (0.31 sec)
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tensorflow/compiler/mlir/tensorflow/ir/tf_ops_a_m.cc
int64_t out_row_dim = output_shape[output_shape.size() - 2]; int64_t out_col_dim = output_shape[output_shape.size() - 1]; int64_t expected_out_row_dim = op.getAdjX() ? x_col_dim : x_row_dim; int64_t expected_out_col_dim = op.getAdjY() ? y_row_dim : y_col_dim; if (expected_out_row_dim != ShapedType::kDynamic && out_row_dim != ShapedType::kDynamic && out_row_dim != expected_out_row_dim)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 146.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_ops.td
Variadic<TF_Tensor>:$output ); TF_DerivedOperandTypeListAttr Tin = TF_DerivedOperandTypeListAttr<1>; TF_DerivedResultTypeListAttr Tout = TF_DerivedResultTypeListAttr<0>; TF_DerivedResultShapeListAttr output_shapes = TF_DerivedResultShapeListAttr<0>; let hasCanonicalizer = 1; let hasVerifier = 1; let extraClassDeclaration = [{ int num_branches() { return getBranches().size(); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Apr 24 04:08:35 UTC 2024 - 90.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/order_by_dialect.mlir
return %arg0 : tensor<!tf_type.variant> } // CHECK-LABEL: iterators func.func private @iterators(%arg0 : tensor<!tf_type.variant>) { %0 = "tf.Iterator"() {container = "", output_shapes = [#tf_type.shape<200x28x28x1>, #tf_type.shape<200x10>], output_types = [f32, f32], shared_name = "_iterator1"} : () -> tensor<!tf_type.resource> %1 = func.call @id(%arg0) : (tensor<!tf_type.variant>) -> tensor<!tf_type.variant>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 7.6K bytes - Viewed (0) -
tensorflow/compiler/jit/xla_launch_util.cc
const xla::HloInputOutputAliasConfig& input_output_alias, absl::Span<const int> input_mapping, const std::map<int, const Tensor*>& resource_vars_snapshots, DataType output_dtype, const TensorShape& output_shape, Allocator* output_allocator, bool allocate_xla_tensors, se::Stream* stream, bool use_multiple_streams, std::shared_ptr<se::Event> definition_event) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 16 00:36:08 UTC 2024 - 40.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/utils/convert_tensor.cc
return ConvertTensor(t, builder); } void ConvertToTensorShapeProto(ArrayRef<int64_t> shape, TensorShapeProto* output_shape) { for (auto d : shape) { output_shape->add_dim()->set_size(ShapedType::isDynamic(d) ? kTFDynamicSize : d); } }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Apr 26 09:37:10 UTC 2024 - 20.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/quantize.mlir
%output_shape = arith.constant dense<[2, 3, 2, 2048]> : tensor<4xi32> %f16_weights = "tfl.pseudo_const"() {value = dense<1.0> : tensor<4x2x2x2048xf16>} : () -> tensor<4x2x2x2048xf16> %dq_weights = "tfl.dequantize"(%f16_weights) : (tensor<4x2x2x2048xf16>) -> tensor<4x2x2x2048xf32> %bias = "tfl.no_value"() {value} : () -> none
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 23:10:13 UTC 2024 - 39.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/shape_inference.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jan 23 17:24:10 UTC 2024 - 167.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo.cc
} auto output_shape = mlir::cast<RankedTensorType>(conv_op.getResult().getType()) .getShape(); SmallVector<int64_t, 4> transposed_output_shape = { output_shape[dnums.getOutputBatchDimension()], output_shape[dnums.getOutputSpatialDimensions().data()[0]], output_shape[dnums.getOutputSpatialDimensions().data()[1]],
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 154.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/optimize.cc
mlir::cast<ShapedType>(input.getType()).getShape(); ArrayRef<int64_t> output_shape = mlir::cast<ShapedType>(output.getType()).getShape(); int64_t agg_value = 1; for (size_t i = agg_start_idx; i < input_shape.size() - 1; ++i) { agg_value *= input_shape[i]; } return (agg_value == output_shape[agg_start_idx]); } // Returns whether the given type `a` is broadcast-compatible with `b`.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 102.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/flatbuffer_import.cc
for (auto s : new_shape) { shape.push_back( builder.getI32IntegerAttr(mlir::TFL::ConvertToTfliteSize(s))); } auto output_shape = DenseElementsAttr::get(shape_type, shape); auto shape_op = builder.create<tfl::ConstOp>(loc, output_shape); op_state.addOperands({shape_op}); } op_state.addTypes({type}); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 21 18:21:50 UTC 2024 - 66.8K bytes - Viewed (0)