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Results 1 - 10 of 13 for _output_shapes (0.22 sec)
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tensorflow/compiler/mlir/lite/tests/prepare-composite-functions-tf.mlir
%4 = "tf.Add"(%2, %arg2) : (tensor<?x8x10xf32>, tensor<8x10xf32>) -> tensor<?x8x10xf32> %5 = "tf.Add"(%arg1, %arg2) : (tensor<8x10xf32>, tensor<8x10xf32>) -> tensor<8x10xf32> %6 = "tf.Const"() {_output_shapes = ["tfshape$"], device = "/device:CPU:0", dtype = f32, value = dense<1.000000e+00> : tensor<f32>} : () -> tensor<f32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 122.1K bytes - Viewed (0) -
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/lite/ir/tfl_ops.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 May 02 09:41:17 UTC 2024 - 169.2K 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/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/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/tensorflow/tests/canonicalize.mlir
%4 = "tf.Case"(%2, %arg0, %arg1) {branches = [@sub, @add], output_shapes = [#tf_type.shape<>], device = "noodle", is_stateless = false} : (tensor<i32>, tensor<f32>, tensor<f32>) -> tensor<f32> // CHECK: PartitionedCall // CHECK-SAME: f = @sub // CHECK-SAME: _cluster_launch = "not_ready" // CHECK-SAME: device = "noodle"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 22:07:10 UTC 2024 - 132.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/uniform_quantized_stablehlo_to_tfl_pass.cc
.getScale(), /*filter_scales=*/filter_quantized_type.getScales()); const ArrayRef<int64_t> output_shape = op->getResult(0).getType().cast<TensorType>().getShape(); const SmallVector<int64_t, 1> bias_shape = { output_shape[output_shape.size() - 1]}; // `tfl.fully_connected`'s `GetChannelDimIndex` is 0. const auto bias_quantized_type =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 22 09:00:19 UTC 2024 - 99.8K bytes - Viewed (0)