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Results 71 - 80 of 111 for _output_shapes (0.3 sec)
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tensorflow/compiler/mlir/tfrt/tests/mlrt/tf_to_mlrt.mlir
%2 = "tf.Const"() {__op_key = 2: i32, device = "/device:CPU:0", value = dense<1> : tensor<i64>} : () -> tensor<i64> %3 = "tf.RangeDataset"(%0, %1, %2) {__op_key = 3: i32, device = "/device:CPU:0", output_shapes = [#tf_type.shape<>], output_types = [i64], metadata = ""} : (tensor<i64>, tensor<i64>, tensor<i64>) -> tensor<!tf_type.variant> // CHECK: tf_mlrt.executeop{{.*}}op: \22FlatMapDataset\22
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 31 20:44:15 UTC 2024 - 24.7K bytes - Viewed (0) -
tensorflow/c/c_api_experimental.cc
continue; } shape.dims = new int64_t[shape.num_dims]; for (size_t j = 0; j < shape.num_dims; ++j) { shape.dims[j] = c.Value(c.Dim(shape_handle, j)); } } if (output_shapes != nullptr) *output_shapes = output_shapes_result; // TODO(bgogul): Set output_resource_shapes_and_types. } void TF_ImportGraphDefOptionsSetValidateColocationConstraints(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 15 03:35:10 UTC 2024 - 29.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/shape_inference.cc
} auto output_shape = xla::ShapeInference::InferGatherShape( input_shape, start_indices_shape, gather_dim_numbers, slice_sizes); if (!output_shape.ok()) { op->emitError() << output_shape.status().message(); return false; } auto refined_type = xla::ConvertShapeToType<RankedTensorType>( *output_shape, mlir::Builder(op)); if (!refined_type.ok()) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Jun 08 07:28:49 UTC 2024 - 134.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/device_index_selector.cc
// // ```mlir // %1 = "tf.DeviceIndex"() // {device = "", device_names = ["CPU", "GPU"]} : () -> tensor<i32> // %4 = "tf.Case"(%1, %arg0, %arg1) // {branches = [@foo, @baz], output_shapes = [#tf_type.shape<>]} : // (tensor<i32>, tensor<f32>, tensor<f32>) -> tensor<f32> // ``` // // Shows an example where there are 2 different functions which could be
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Nov 03 12:35:38 UTC 2022 - 3.4K 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/c/c_api_experimental.h
// - The types need not be set in `input_shapes` as it is not used. // - The number of `input_tensors` should be the same as the number of items // in `input_shapes`. // // The results are returned in `output_shapes` and // `output_resource_shapes_and_types`. The caller is responsible for freeing the // memory in these buffers by calling `TF_DeleteShapeAndTypeList`. TF_CAPI_EXPORT extern void TFE_InferShapes(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 27 21:07:00 UTC 2023 - 15.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/localize_var_handles.mlir
return %0 : tensor<200x10xf32> } // CHECK-LABEL: @main func.func @main() attributes {tf_saved_model.exported_names = ["main"]} { %0 = "tf.Iterator"() {container = "", output_shapes = [#tf_type.shape<200x10>], output_types = [f32], shared_name = "foo_iterator"} : () -> tensor<!tf_type.resource> %1 = func.call @get_next(%0) : (tensor<!tf_type.resource>) -> tensor<200x10xf32> return } }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Aug 23 21:12:02 UTC 2023 - 10.3K 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_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)