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Results 11 - 20 of 63 for _output_shapes (0.62 sec)
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tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test.py
) ] ) ) self.assertTrue( self._contains_op( output_graphdef, 'Const', '_output_shapes', per_channel_size_attr, ) ) elif target_opset == quant_opts_pb2.UNIFORM_QUANTIZED: self.assertTrue(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 03:36:50 UTC 2024 - 235.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/translate/import_model.cc
if (node.IsWhileNode()) { auto* output_shapes = node.attrs().Find("output_shapes"); auto* element_types = node.attrs().Find("T"); if (output_shapes && !output_shapes->list().shape().empty()) { const auto& output_shape = output_shapes->list().shape(idx); const auto& element_type = element_types->list().type(idx); return ConvertToMlirTensorType(output_shape, element_type, &builder); } }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 01 11:17:36 UTC 2024 - 183.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/translate/export_graphdef.cc
(*node_def->mutable_attr())["_handle_dtypes"] = handle_dtypes_attr; (*node_def->mutable_attr())["_handle_shapes"] = handle_shapes_attr; } } TF_RETURN_IF_ERROR( SetShapeAttribute("_output_shapes", arg_type, node_def->mutable_attr())); DataType dtype; TF_RETURN_IF_ERROR(ConvertToDataType(arg_type.getElementType(), &dtype)); AttrValue type_attr; type_attr.set_type(dtype);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 01 11:17:36 UTC 2024 - 35.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/api/v2/tf_executor_to_graph.cc
(*node_def->mutable_attr())["_handle_dtypes"] = handle_dtypes_attr; (*node_def->mutable_attr())["_handle_shapes"] = handle_shapes_attr; } } TF_RETURN_IF_ERROR( SetShapeAttribute("_output_shapes", arg_type, node_def->mutable_attr())); DataType dtype; TF_RETURN_IF_ERROR(ConvertToDataType(arg_type.getElementType(), &dtype)); AttrValue type_attr; type_attr.set_type(dtype);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 23:04:51 UTC 2024 - 35.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/api/v1/compile_mlir_util.cc
// the shape inference pass is run early in the pass pipeline, shape inference // during import is not necessary. config.enable_shape_inference = false; // Some graphs may require _output_shapes (an unregistered attribute) // to override shapes. It is unfortunately not always set correctly so only // do it optionally. config.unconditionally_use_set_output_shapes =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 21 17:24:39 UTC 2024 - 45.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf.mlir
// CHECK-DAG: [[LINSPACE:%.*]] = chlo.broadcast_add [[MUL]], [[START]] {broadcast_dimensions = array<i64>} // CHECK: return [[LINSPACE]] %0 = "tf.Const"() {_output_shapes = ["tfshape$"], device = "", dtype = i32, value = dense<4> : tensor<i32>} : () -> tensor<i32> %1 = "tf.LinSpace"(%arg0, %arg1, %0) : (tensor<f32>, tensor<f32>, tensor<i32>) -> tensor<4xf32> func.return %1 : tensor<4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 06 18:46:23 UTC 2024 - 335.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/constant-fold.mlir
func.func @testUnimplementedOp() -> (tensor<i32>, tensor<i32>) { %0 = arith.constant dense<1> : tensor<i32> %1 = arith.constant dense<2> : tensor<i32> %2 = "tf.Maximum"(%0, %1) {_output_shapes = ["tfshape$"]} : (tensor<i32>, tensor<i32>) -> tensor<i32> %3 = "tf.Minimum"(%0, %1) {random_attr = "hello"} : (tensor<i32>, tensor<i32>) -> tensor<i32> func.return %2, %3: tensor<i32>, tensor<i32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jan 31 23:22:24 UTC 2024 - 36.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/lstm_utils_test.cc
SmallVector<int64_t, 2> output_shape{1, mlir::ShapedType::kDynamic}; EXPECT_EQ(mlir::cast<RankedTensorType>(output_types[0]).getShape().size(), output_shape.size()); for (int i = 0; i < output_shape.size(); i++) { EXPECT_EQ(mlir::cast<RankedTensorType>(output_types[0]).getDimSize(i), output_shape[i]); } }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 10K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/composite_utils.cc
std::array<int64_t, 4> output_shape; // NHWC <- NCHW output_shape[0] = composite_result_shape[0]; output_shape[1] = composite_result_shape[2]; output_shape[2] = composite_result_shape[3]; output_shape[3] = composite_result_shape[1]; auto input_type = mlir::cast<ShapedType>(old_op->getOperand(0).getType()); return RankedTensorType::get(output_shape, input_type.getElementType()); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 29 18:33:05 UTC 2024 - 3.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/quantize_patterns.td
// Transpose conv supports hybrid computation with quantized weights. def FoldQuantWeightsIntoTposeConv : Pat< (TFL_TransposeConvOp $output_shape, (TFL_DequantizeOp $quant_weights), $quant_input, $bias, $padding, $stride_h, $stride_w, $faf), (TFL_TransposeConvOp $output_shape, $quant_weights, $quant_input, $bias, $padding, $stride_h, $stride_w, $faf),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 23:10:13 UTC 2024 - 2.3K bytes - Viewed (0)