support uniform & fix some tests

paddle2onnx/mapper/tensor/uniform.cc

@@ -0,0 +1,57 @@
+// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "paddle2onnx/mapper/tensor/uniform.h"
+
+namespace paddle2onnx {
+REGISTER_PIR_MAPPER(uniform, UniformMapper)
+
+int32_t UniformMapper::GetMinOpsetVersion(bool verbose) { return 7; }
+
+void UniformMapper::Opset7() {
+  auto output_info = GetOutput("out");
+  auto shape_info = GetInput("shape");
+  auto min_info = GetInput("min");
+  auto max_info = GetInput("max");
+
+  if (min_info[0].Rank() != 0 || max_info[0].Rank() != 0) {
+    Error() << "[ERROR] min/max must be scalar tensors for op "
+               "uniform "
+            << std::endl;
+  }
+  std::vector<float> min_val{0.0f}, max_val{1.0f};
+  bool is_min_const =
+      helper_->TryGetTensorValue<float>(min_info[0].name, &min_val);
+  bool is_max_const =
+      helper_->TryGetTensorValue<float>(max_info[0].name, &max_val);
+
+  std::vector<int64_t> shape_values;
+  helper_->TryGetTensorValue<int64_t>(shape_info[0].name, &shape_values);
+
+  auto onnx_dtype = GetOnnxDtype(dtype_);
+
+  auto random_node =
+      helper_->MakeNode("RandomUniform", {}, {output_info[0].name});
+
+  AddAttribute(random_node, "shape", shape_values);
+  AddAttribute(random_node, "low", min_val[0]);
+  AddAttribute(random_node, "high", max_val[0]);
+  AddAttribute(random_node, "dtype", static_cast<int64_t>(onnx_dtype));
+  if (seed_ != 0) {
+    AddAttribute(random_node, "seed", static_cast<float>(seed_));
+  }
+
+  std::cout << "dtype_" << dtype_ << std::endl;
+}
+}  // namespace paddle2onnx

paddle2onnx/mapper/tensor/uniform.h

@@ -0,0 +1,39 @@
+// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+#include <string>
+#include <vector>
+
+#include "paddle2onnx/mapper/mapper.h"
+
+namespace paddle2onnx {
+
+class UniformMapper : public Mapper {
+ public:
+  UniformMapper(const PaddlePirParser& p, OnnxHelper* helper, int64_t i, bool c)
+      : Mapper(p, helper, i, c) {
+    GetAttr("dtype", &dtype_);
+    GetAttr("seed", &seed_);
+  }
+
+  int32_t GetMinOpsetVersion(bool verbose) override;
+  void Opset7() override;
+
+ private:
+  int64_t dtype_;
+  int64_t seed_;
+};
+
+}  // namespace paddle2onnx

tests/onnxbase.py

@@ -21,7 +21,7 @@
 import paddle
 import paddle2onnx
 import paddle.static as static
-from paddle2onnx.convert import dygraph2onnx, decompose_program
+from paddle2onnx.convert import dygraph2onnx
 import shutil
 from functools import wraps
 
@@ -232,8 +232,6 @@ def __init__(
         self.input_spec_shape = input_spec_shape
         self.input_dtype = []
         self.res_fict = {}
-        self.dist_prim_all = False
-        self.auto_upgrade_opset = False
 
         if isfunction(self.func):
             # self._func = self.BuildFunc(self.func, **self.kwargs_dict_dygraph["params_group1"])
@@ -497,10 +495,7 @@ def run(self):
             # clip extra
             model_file = None
             if paddle.get_flags("FLAGS_enable_pir_api")["FLAGS_enable_pir_api"]:
-                if self.dist_prim_all and self.auto_upgrade_opset:
-                    model_file = decompose_program(original_model_file)
-                else:
-                    model_file = original_model_file
+                model_file = original_model_file
             else:
                 model_file = os.path.join(self.name, "cliped_model.pdmodel")
                 self.clip_extra_program_only(original_model_file, model_file)

tests/run.bat

@@ -35,26 +35,16 @@ set ignore=test_auto_scan_multiclass_nms.py
 set ignore=!ignore! test_auto_scan_roi_align.py
 set ignore=!ignore! test_auto_scan_pool_adaptive_max_ops.py
 set ignore=!ignore! test_auto_scan_pad2d.py
-set ignore=!ignore! test_auto_scan_roll.py
 set ignore=!ignore! test_auto_scan_unfold.py
 set ignore=!ignore! test_auto_scan_uniform_random_batch_size_like.py
 set ignore=!ignore! test_auto_scan_uniform_random.py
-set ignore=!ignore! test_auto_scan_dist.py
 set ignore=!ignore! test_auto_scan_distribute_fpn_proposals1.py
 set ignore=!ignore! test_auto_scan_distribute_fpn_proposals_v2.py
 set ignore=!ignore! test_auto_scan_fill_constant_batch_size_like.py
 set ignore=!ignore! test_auto_scan_generate_proposals.py
 set ignore=!ignore! test_uniform.py
-set ignore=!ignore! test_ceil.py
 set ignore=!ignore! test_deform_conv2d.py
-set ignore=!ignore! test_floor_divide.py
 set ignore=!ignore! test_has_nan.py
-set ignore=!ignore! test_median.py
-set ignore=!ignore! test_nn_GroupNorm.py
-set ignore=!ignore! test_nn_InstanceNorm3D.py
-set ignore=!ignore! test_nn_Upsample.py
-set ignore=!ignore! test_normalize.py
-set ignore=!ignore! test_scatter_nd_add.py
 set ignore=!ignore! test_unsqueeze.py
 set ignore=!ignore! test_quantize_model.py
 set ignore=!ignore! test_quantize_model_minist.py
@@ -72,7 +62,6 @@ set ignore=!ignore! test_auto_scan_conv2d.py
 set ignore=!ignore! test_auto_scan_conv2d_transpose.py
 set ignore=!ignore! test_auto_scan_conv3d.py
 set ignore=!ignore! test_auto_scan_grid_sampler.py
-set ignore=!ignore! test_auto_scan_set_value.py
 set ignore=!ignore! test_auto_scan_dequantize_linear.py
 set ignore=!ignore! test_auto_scan_gaussian_random.py
 set ignore=!ignore! test_auto_scan_partial_ops.py

tests/run.sh

@@ -29,30 +29,19 @@ ignore="test_auto_scan_multiclass_nms.py
         test_auto_scan_roi_align.py \ # need to be rewrite
         test_auto_scan_pool_adaptive_max_ops.py \
         test_auto_scan_pad2d.py \
-        test_auto_scan_roll.py \
         test_auto_scan_unfold.py \
         test_auto_scan_uniform_random_batch_size_like.py \
         test_auto_scan_uniform_random.py \
         test_auto_scan_gaussian_random.py \
-        test_auto_scan_dist.py \
         test_auto_scan_distribute_fpn_proposals1.py \
         test_auto_scan_distribute_fpn_proposals_v2.py \
         test_auto_scan_fill_constant_batch_size_like.py \
         test_auto_scan_unary_ops.py \
         test_auto_scan_generate_proposals.py \
         test_uniform.py \
-        test_ceil.py \
         test_deform_conv2d.py \
-        test_floor_divide.py \
-        test_has_nan.py \
-        test_median.py \
-        test_nn_GroupNorm.py \
-        test_nn_InstanceNorm3D.py \
-        test_nn_Upsample.py \
-        test_normalize.py \
         test_hardtanh.py \
         test_nn_GRU.py \
-        test_scatter_nd_add.py \
         test_quantize_model.py \
         test_quantize_model_minist.py \
         test_auto_scan_partial_ops.py \
@@ -63,8 +52,7 @@ ignore="test_auto_scan_multiclass_nms.py
         test_resnet_fp16.py \
         test_empty.py \
         test_auto_scan_pool_max_ops.py \
-        test_auto_scan_fill_constant.py \
-        test_auto_scan_set_value.py"
+        test_auto_scan_fill_constant.py"
 bug=0
 
 # Install Python Packet

tests/test_auto_scan_roll.py

@@ -16,7 +16,7 @@
 import hypothesis.strategies as st
 import unittest
 import paddle
-from onnxbase import _test_only_pir
+from onnxbase import _test_with_pir
 
 
 class Net(BaseNet):
@@ -112,7 +112,7 @@ def sample_convert_config(self, draw):
 
         return (config, models)
 
-    @_test_only_pir
+    @_test_with_pir
     def test(self):
         self.run_and_statis(max_examples=80)
 

tests/test_auto_scan_set_value.py

@@ -16,7 +16,7 @@
 import hypothesis.strategies as st
 import unittest
 import copy
-from onnxbase import _test_only_pir
+from onnxbase import _test_with_pir
 
 
 # TODO(wangmingkai02): add test for set_value which none_axes_ > 0
@@ -62,7 +62,7 @@ def sample_convert_config(self, draw):
 
         return (config, models)
 
-    @_test_only_pir
+    @_test_with_pir
     def test(self):
         self.run_and_statis(max_examples=30)
 

tests/test_nn_GroupNorm.py

@@ -13,8 +13,7 @@
 # limitations under the License.
 
 import paddle
-from onnxbase import APIOnnx
-from onnxbase import randtool
+from onnxbase import APIOnnx, randtool, _test_with_pir
 
 
 class Net(paddle.nn.Layer):
@@ -34,6 +33,7 @@ def forward(self, inputs):
         return x
 
 
+@_test_with_pir
 def test_GroupNorm_11():
     """
     api: paddle.nn.GroupNorm
@@ -42,14 +42,15 @@ def test_GroupNorm_11():
     op = Net()
     op.eval()
     # net, name, ver_list, delta=1e-6, rtol=1e-5
-    obj = APIOnnx(op, 'nn_GroupNorm', [11])
+    obj = APIOnnx(op, "nn_GroupNorm", [11])
     obj.set_input_data(
         "input_data",
-        paddle.to_tensor(
-            randtool("float", -1, 1, [5, 10, 8, 8]).astype('float32')))
+        paddle.to_tensor(randtool("float", -1, 1, [5, 10, 8, 8]).astype("float32")),
+    )
     obj.run()
 
 
+@_test_with_pir
 def test_GroupNorm_12():
     """
     api: paddle.nn.GroupNorm
@@ -58,9 +59,9 @@ def test_GroupNorm_12():
     op = Net()
     op.eval()
     # net, name, ver_list, delta=1e-6, rtol=1e-5
-    obj = APIOnnx(op, 'nn_GroupNorm', [12])
+    obj = APIOnnx(op, "nn_GroupNorm", [12])
     obj.set_input_data(
         "input_data",
-        paddle.to_tensor(
-            randtool("float", -1, 1, [5, 10, 8, 8]).astype('float32')))
+        paddle.to_tensor(randtool("float", -1, 1, [5, 10, 8, 8]).astype("float32")),
+    )
     obj.run()

tests/test_nn_InstanceNorm3D.py

@@ -13,8 +13,7 @@
 # limitations under the License.
 
 import paddle
-from onnxbase import APIOnnx
-from onnxbase import randtool
+from onnxbase import APIOnnx, randtool, _test_with_pir
 
 
 class Net(paddle.nn.Layer):
@@ -31,7 +30,8 @@ def __init__(self):
             weight_attr=None,
             bias_attr=None,
             data_format="NCDHW",
-            name=None)
+            name=None,
+        )
 
     def forward(self, inputs):
         """
@@ -41,6 +41,7 @@ def forward(self, inputs):
         return x
 
 
+@_test_with_pir
 def test_InstanceNorm_base():
     """
     api: paddle.InstanceNorm
@@ -49,9 +50,9 @@ def test_InstanceNorm_base():
     op = Net()
     op.eval()
     # net, name, ver_list, delta=1e-6, rtol=1e-5
-    obj = APIOnnx(op, 'nn_InstanceNorm', [9, 10, 11, 12])
+    obj = APIOnnx(op, "nn_InstanceNorm", [9, 10, 11, 12])
     obj.set_input_data(
         "input_data",
-        paddle.to_tensor(
-            randtool("float", -1, 1, [2, 2, 2, 2, 3]).astype('float32')))
+        paddle.to_tensor(randtool("float", -1, 1, [2, 2, 2, 2, 3]).astype("float32")),
+    )
     obj.run()