Merge branch 'yi3/update_to_latest' into new_API

ngraph/frontend/paddlepaddle/src/op/fill_constant_batch_size_like.cpp

@@ -0,0 +1,43 @@
+//*****************************************************************************
+// Copyright 2017-2021 Intel Corporation
+//
+// 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 <ngraph/opsets/opset6.hpp>
+#include "fill_constant_batch_size_like.hpp"
+#include <paddlepaddle_frontend/utility.hpp>
+
+namespace ngraph {
+namespace frontend {
+namespace pdpd {
+namespace op {
+
+NamedOutputs fill_constant_batch_size_like (const NodeContext& node) {
+    auto input_dim_idx = node.get_attribute<int32_t>("input_dim_idx");
+    auto output_dim_idx = node.get_attribute<int32_t>("output_dim_idx");
+    auto value = node.get_attribute<float>("value");
+    auto shapes = node.get_attribute<std::vector<int32_t> >("shape");
+    auto input = node.get_ng_input("Input");
+    auto parial_shape = input.get_partial_shape();
+    PDPD_ASSERT(parial_shape.is_static(), "fill_constant_batch_size_like: must use static shape.");
+    auto static_shape = parial_shape.get_shape();
+    PDPD_ASSERT(input_dim_idx < (int32_t)static_shape.size(), "fill_constant_batch_size_like: input_dim_idx should not exceed input dims.");
+    PDPD_ASSERT(output_dim_idx < (int32_t)shapes.size(), "fill_constant_batch_size_like: output_dim_idx should not exceed shapes dims.");
+    shapes[output_dim_idx] = static_shape[input_dim_idx];
+    return node.default_single_output_mapping(
+        {std::make_shared<ngraph::opset6::Constant>(ngraph::element::f32, Shape(shapes.begin(), shapes.end()), value)}, 
+        {"Out"});
+}
+
+}}}}

ngraph/frontend/paddlepaddle/src/op/fill_constant_batch_size_like.hpp

@@ -0,0 +1,27 @@
+//*****************************************************************************
+// Copyright 2017-2021 Intel Corporation
+//
+// 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 "node_context.hpp"
+
+namespace ngraph {
+namespace frontend {
+namespace pdpd {
+namespace op {
+
+NamedOutputs fill_constant_batch_size_like (const NodeContext& node);
+
+}}}}

ngraph/frontend/paddlepaddle/src/op/greater_equal.cpp

@@ -0,0 +1,32 @@
+//*****************************************************************************
+// Copyright 2017-2021 Intel Corporation
+//
+// 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 <ngraph/opsets/opset6.hpp>
+#include "greater_equal.hpp"
+#include <paddlepaddle_frontend/utility.hpp>
+
+namespace ngraph {
+namespace frontend {
+namespace pdpd {
+namespace op {
+
+NamedOutputs greater_equal (const NodeContext& node) {
+    auto x = node.get_ng_input("X");
+    auto y = node.get_ng_input("Y");
+    return node.default_single_output_mapping({std::make_shared<ngraph::opset6::GreaterEqual>(x, y)}, {"Out"});
+}
+
+}}}}

ngraph/frontend/paddlepaddle/src/op/greater_equal.hpp

@@ -0,0 +1,27 @@
+//*****************************************************************************
+// Copyright 2017-2021 Intel Corporation
+//
+// 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 "node_context.hpp"
+
+namespace ngraph {
+namespace frontend {
+namespace pdpd {
+namespace op {
+
+NamedOutputs greater_equal (const NodeContext& node);
+
+}}}}

ngraph/frontend/paddlepaddle/src/op/log.cpp

@@ -0,0 +1,31 @@
+//*****************************************************************************
+// Copyright 2017-2021 Intel Corporation
+//
+// 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 <ngraph/opsets/opset6.hpp>
+#include "log.hpp"
+#include <paddlepaddle_frontend/utility.hpp>
+
+namespace ngraph {
+namespace frontend {
+namespace pdpd {
+namespace op {
+
+NamedOutputs log (const NodeContext& node) {
+    auto x = node.get_ng_input("X");
+    return node.default_single_output_mapping({std::make_shared<ngraph::opset6::Log>(x)}, {"Out"});     
+}
+
+}}}}

ngraph/frontend/paddlepaddle/src/op/log.hpp

@@ -0,0 +1,27 @@
+//*****************************************************************************
+// Copyright 2017-2021 Intel Corporation
+//
+// 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 "node_context.hpp"
+
+namespace ngraph {
+namespace frontend {
+namespace pdpd {
+namespace op {
+
+NamedOutputs log (const NodeContext& node);
+
+}}}}

ngraph/frontend/paddlepaddle/src/op_table.cpp

@@ -47,7 +47,9 @@
 #include "op/slice.hpp"
 #include "op/hard_swish.hpp"
 #include "op/clip.hpp"
-
+#include "op/greater_equal.hpp"
+#include "op/log.hpp"
+#include "op/fill_constant_batch_size_like.hpp"
 #include "op_table.hpp"
 
 
@@ -99,7 +101,10 @@ std::map<std::string, CreatorFunction> get_supported_ops() {
             {"unsqueeze2", op::unsqueeze},
             {"slice", op::slice},
             {"hard_swish", op::hard_swish},
-            {"clip", op::clip}
+            {"clip", op::clip},
+            {"greater_equal", op::greater_equal},
+            {"log", op::log},
+            {"fill_constant_batch_size_like", op::fill_constant_batch_size_like}
         };
 };
 

ngraph/test/files/paddlepaddle/gen_scripts/generate_fill_constant.py

@@ -0,0 +1,32 @@
+#
+# fill_const paddle model generator
+#
+import numpy as np
+from save_model import saveModel
+import paddle as pdpd
+
+data_type = 'float32'
+
+def fill_constant(name : str, shape : list, dtype, value):
+    pdpd.enable_static()
+
+    with pdpd.static.program_guard(pdpd.static.Program(), pdpd.static.Program()):
+        out = pdpd.fluid.layers.fill_constant(shape=shape, value=value, dtype=dtype, name='fill_constant')
+
+        cpu = pdpd.static.cpu_places(1)
+        exe = pdpd.static.Executor(cpu[0])
+        # startup program will call initializer to initialize the parameters.
+        exe.run(pdpd.static.default_startup_program())
+
+        outs = exe.run(
+            fetch_list=[out])             
+
+        saveModel(name, exe, feedkeys=[], fetchlist=[out], inputs=[], outputs=[outs[0]])
+
+    return outs[0]
+
+def main():
+    fill_constant("fill_constant", [2, 3, 4], data_type, 0.03)
+
+if __name__ == "__main__":
+    main()

ngraph/test/files/paddlepaddle/gen_scripts/generate_fill_constant_batch_size_like.py

@@ -0,0 +1,38 @@
+#
+# fill_constant_batch_size_like paddle model generator
+#
+import numpy as np
+from save_model import saveModel
+import paddle as pdpd
+
+data_type = 'float32'
+
+def fill_constant_batch_size_like(name : str, x, shape, dtype, value, input_dim_idx=0, output_dim_idx=0):
+    pdpd.enable_static()
+
+    with pdpd.static.program_guard(pdpd.static.Program(), pdpd.static.Program()):
+        like = pdpd.static.data(name='x', shape=x.shape, dtype = data_type)
+        out = pdpd.fluid.layers.fill_constant_batch_size_like(input=like, shape=shape, \
+            value=value, dtype=dtype, \
+            output_dim_idx=output_dim_idx, input_dim_idx=input_dim_idx)
+
+        cpu = pdpd.static.cpu_places(1)
+        exe = pdpd.static.Executor(cpu[0])
+        # startup program will call initializer to initialize the parameters.
+        exe.run(pdpd.static.default_startup_program())
+
+        outs = exe.run(
+            feed={'x': x},
+            fetch_list=[out])
+
+        saveModel(name, exe, feedkeys=['x'], fetchlist=[out], inputs=[x], outputs=[outs[0]])
+
+    return outs[0]
+
+def main():
+    x = np.random.rand(4, 3, 2).astype(data_type)
+    fill_constant_batch_size_like("fill_constant_batch_size_like", \
+        x, [1, -1, 3], data_type, 0.03, 2, 1)
+
+if __name__ == "__main__":
+    main()

ngraph/test/files/paddlepaddle/gen_scripts/generate_greater_equal.py

@@ -0,0 +1,40 @@
+#
+# greater_equal paddle model generator
+#
+import numpy as np
+from save_model import saveModel
+import paddle as pdpd
+
+data_type = 'float32'
+
+def greater_equal(name : str, x, y):
+    pdpd.enable_static()
+
+    with pdpd.static.program_guard(pdpd.static.Program(), pdpd.static.Program()):
+        node_x = pdpd.static.data(name='x', shape=x.shape, dtype = data_type)
+        node_y = pdpd.static.data(name='y', shape=y.shape, dtype = data_type)
+        out = pdpd.fluid.layers.greater_equal(x=node_x, y=node_y, name='greater_equal')
+        # save model does not support boolean type
+        out = pdpd.cast(out, data_type)
+
+        cpu = pdpd.static.cpu_places(1)
+        exe = pdpd.static.Executor(cpu[0])
+        # startup program will call initializer to initialize the parameters.
+        exe.run(pdpd.static.default_startup_program())
+
+        outs = exe.run(
+            feed={'x': x, 'y' : y},
+            fetch_list=[out])
+
+        saveModel(name, exe, feedkeys=['x', 'y'], fetchlist=[out], inputs=[x, y], outputs=[outs[0]])
+
+    return outs[0]
+
+def main():
+    x = np.array([0, 1, 2, 3]).astype(data_type)
+    y = np.array([1, 0, 2, 4]).astype(data_type)
+
+    greater_equal("greater_equal", x, y)
+
+if __name__ == "__main__":
+    main()

ngraph/test/files/paddlepaddle/gen_scripts/generate_log.py

@@ -0,0 +1,36 @@
+#
+# log paddle model generator
+#
+import numpy as np
+from save_model import saveModel
+import paddle as pdpd
+
+data_type = 'float32'
+
+def log(name : str, x):
+    pdpd.enable_static()
+
+    with pdpd.static.program_guard(pdpd.static.Program(), pdpd.static.Program()):
+        node_x = pdpd.static.data(name='x', shape=x.shape, dtype = data_type)
+        out = pdpd.fluid.layers.log(node_x, name = 'log')
+
+        cpu = pdpd.static.cpu_places(1)
+        exe = pdpd.static.Executor(cpu[0])
+        # startup program will call initializer to initialize the parameters.
+        exe.run(pdpd.static.default_startup_program())
+
+        outs = exe.run(
+            feed={'x': x},
+            fetch_list=[out])             
+
+        saveModel(name, exe, feedkeys=['x'], fetchlist=[out], inputs=[x], outputs=[outs[0]])
+
+    return outs[0]
+
+def main():
+    x = np.array([0, 1, 2, -10]).astype(data_type)
+
+    log("log", x)
+
+if __name__ == "__main__":
+    main()