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Results 101 - 110 of 112 for ShapedType (0.17 sec)
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tensorflow/compiler/mlir/lite/transforms/lower_static_tensor_list.cc
// Here we assume that the element_shape won't be changed before calling // the first `TensorListSetItemOp`. if (auto shaped_type = element_shape.getType().dyn_cast<ShapedType>()) { if (shaped_type.hasRank() && shaped_type.getRank() == 0) { bool element_shape_acquired = false; auto uses = op.getResult().getUses(); for (auto &use : llvm::make_early_inc_range(uses)) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 20:00:43 UTC 2024 - 70.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/einsum.cc
int64_t prod_shape = 1; for (auto index_tuple : index_tuples) { const int64_t shape_i = shape[std::get<I>(index_tuple)]; if (ShapedType::isDynamic(shape_i)) return ShapedType::kDynamic; prod_shape *= shape_i; } return prod_shape; } // Reshapes LHS and RHS to have B0,...,Bn,L,C and B0,...,Bn,C,R shape
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 33.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/uniform_quantized_stablehlo_to_tfl_pass.cc
const auto [input_height, input_width] = GetDimSize(op->getOperand(0).getType().cast<ShapedType>().getShape(), dimension_numbers.getInputSpatialDimensions()); const auto [output_height, output_width] = GetDimSize(op->getResult(0).getType().cast<ShapedType>().getShape(), dimension_numbers.getOutputSpatialDimensions());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 22 09:00:19 UTC 2024 - 99.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/lift_as_function_call.cc
SmallVector<Attribute> shape_attrs; for (const Type result_type : output_types) { shape_attrs.push_back( tf_type::ShapeAttr::get(ctx, mlir::cast<ShapedType>(result_type))); } auto empty_array_attr = ArrayAttr::get(ctx, {}); auto platforms = ArrayAttr::get(ctx, {StringAttr::get(ctx, kPlatformCpu)}); auto call_op = builder.create<TF::XlaCallModuleOp>(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 17:58:54 UTC 2024 - 21.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/replace_stablehlo_ops_in_main_function_with_xla_call_module_ops.cc
// Create attributes used for creating an XlaCallModuleOp. SmallVector<Attribute> shape_attrs; for (const Type result_type : result_types) { shape_attrs.push_back( tf_type::ShapeAttr::get(ctx, mlir::cast<ShapedType>(result_type))); } const auto empty_array_attr = ArrayAttr::get(ctx, {}); // TODO: b/310291615 - find a better way for platform support. const auto platforms = ArrayAttr::get( ctx,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 21K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/legalize_patterns.td
(TFL_TopKV2Op $input, $k)>; def ReductionDimensionIsLastDim : Constraint<CPred<"($0.cast<IntegerAttr>().getInt() == " "$1.getType().cast<ShapedType>().getRank() - 1 || $0.cast<IntegerAttr>().getInt() == -1)">>; // Legalizes TF_ApproxTopKOp to TFL_TopKV2Op with the following constraints: // 1. It computes max k
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 04 13:30:42 UTC 2024 - 28.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/c/c_api_unified_experimental_mlir.cc
// unified_api_test.cc. return Unimplemented("MlirTensor::Shape is not implemented yet."); } Value getValue() { return value_; } Type getElementType() { return mlir::cast<ShapedType>(value_.getType()).getElementType(); } // For LLVM style RTTI. static bool classof(const AbstractTensorHandle* ptr) { return ptr->getKind() == kMlir; }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 28.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/flatbuffer_import.cc
if (!tensor.quantization || tfl::IsQuantized(tensor)) return nullptr; // If the result isn't float and unquantizable, the min/max is ignored. if (!res.getType() .cast<mlir::ShapedType>() .getElementType() .isa<mlir::FloatType>()) { return nullptr; } auto mins = tensor.quantization->min; auto maxs = tensor.quantization->max;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 21 18:21:50 UTC 2024 - 66.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/quantization_patterns.cc
// `stablehlo.dot_general` legalizable to `tfl.fully_connected` has a // filter rank of 2 with the last dimension as the channel dimension. const int64_t quantization_dimension = mlir::cast<ShapedType>(filter_type).getShape().size() - 1; accumulation_quantized_element_type = CreateI32F32UniformQuantizedPerAxisType( gemm_style_op->getLoc(), *rewriter.getContext(), result_scales,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 03 06:04:36 UTC 2024 - 41.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/api/v1/compile_mlir_util.cc
ranked_ty.getEncoding()); if (encoding && !encoding.getBounds().empty()) { for (int64_t dim = 0; dim < rank; ++dim) { if (dims[dim] == mlir::ShapedType::kDynamic) { dims[dim] = encoding.getBounds()[dim]; } } } return GetTypeFromTFTensorShape(dims, ranked_ty.getElementType()); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 21 17:24:39 UTC 2024 - 45.3K bytes - Viewed (0)