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Results 1 - 7 of 7 for _output_shapes (0.3 sec)
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tensorflow/compiler/mlir/lite/tests/prepare-tf.mlir
%cst_0 = arith.constant dense<1> : tensor<3xi32> %0 = "tf.Squeeze"(%arg0) {T = f32, _output_shapes = ["tfshape$dim { size: 4 } dim { size: 64 } dim { size: 64 }"], device = "", squeeze_dims = []} : (tensor<4x64x64x1xf32>) -> tensor<4x64x64xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 29 07:26:59 UTC 2024 - 59.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/optimize_patterns.td
def FuseBinaryOpWithTransposeConv#binaryOp : Pat< (binaryOp (TFL_TransposeConvOp:$output $output_shape, $weights, $input, (Arith_ConstantOp FloatElementsAttr:$bias), $padding, $stride_h, $stride_w, TFL_AF_None), (Arith_ConstantOp FloatElementsAttr:$value), $act_fn), (TFL_TransposeConvOp $output_shape, $weights, $input, (binaryOp (Arith_ConstantOp $bias),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 16 20:31:41 UTC 2024 - 66.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/lower_static_tensor_list.cc
auto new_shape = rewriter.create<TF::ShapeOp>(loc, shape_type, input); SmallVector<int64_t, 8> output_shape(/*Size=*/1, op.getNumElements()); for (const auto &dim : dense_elem_attr.getValues<APInt>()) output_shape.push_back(dim.getSExtValue()); RankedTensorType result_type = tensorflow::GetTypeFromTFTensorShape( output_shape, getElementTypeOrSelf(input)); rewriter.replaceOpWithNewOp<TF::ReshapeOp>(op, result_type, input,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 20:00:43 UTC 2024 - 70.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/lower_tf.cc
auto begin = rewriter.create<ConstOp>(op->getLoc(), axis_type, begin_attr); SmallVector<int64_t, 4> output_shape; output_shape.append(input_shape.begin(), input_shape.end()); output_shape[axis_i] = size_i; auto size_attr = DenseIntElementsAttr::get(axis_type, output_shape); auto size = rewriter.create<ConstOp>(op->getLoc(), axis_type, size_attr);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 74.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_ops.td
Variadic<TF_Tensor>:$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/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) -
tensorflow/compiler/mlir/tfrt/tests/mlrt/while_to_map_fn.mlir
[i32, i32, i32, !tf_type.variant, !tf_type.variant, f32], _lower_using_switch_merge = true, _num_original_outputs = 6 : i64, _read_only_resource_inputs = [], body = @map_while_body_180, cond = @map_while_cond_170, device = "", is_stateless = true, output_shapes = [#tf_type.shape<>, #tf_type.shape<>, #tf_type.shape<>, #tf_type.shape<>, #tf_type.shape<>, #tf_type.shape<?>], parallel_iterations = 4 : i64, shape_invariant} : (tensor<i32>, tensor<i32>, tensor<i32>, tensor<!tf_type.variant<tensor<*xf32>>>,...
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 23 06:40:22 UTC 2024 - 68.6K bytes - Viewed (0)