Cecilia/fix/slice decrease axis (#8342)

* 1. fix for CVS-69011 2.add more test cases for slice w/ decrease_axis

* add test case simulating the last reshape2 of ocrnet which accepts slice (with decrease_axes in all dims) as its parents.

* exportModel as a helper function.

* fix: rank get_length type

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

@@ -77,9 +77,24 @@ NamedOutputs slice(const NodeContext& node) {
     auto decrease_axis = node.get_attribute<std::vector<int32_t>>("decrease_axis");
 
     if (decrease_axis.size() > 0) {
-        auto squeeze_index_node = Constant::create(element::i32, {}, decrease_axis);
+        // according to paddle slice_op, when all axes are decreased, output shape is [1], instead of scalar.
+        // Ref: paddle/fluid/operators/slice_op.h
+        PartialShape input_shape = data.get_partial_shape();
+        PDPD_OP_VALIDATION_CHECK(node,
+                                 input_shape.rank().is_static(),
+                                 "input rank of slice must be static when decrease_axis is set.");
+
+        auto squeeze_index_node = Constant::create(element::i32, {decrease_axis.size()}, decrease_axis);
         auto decreased_node = std::make_shared<Squeeze>(stride_slice_node, squeeze_index_node);
 
+        auto input_rank = input_shape.rank().get_length();
+        if (input_rank == decrease_axis.size()) {
+            auto restore_node = std::make_shared<Reshape>(decreased_node,
+                                                          std::make_shared<Constant>(element::i64, Shape{1}, 1),
+                                                          false);  // restore to shape (1,)
+            return node.default_single_output_mapping({restore_node}, {"Out"});
+        }
+
         return node.default_single_output_mapping({decreased_node}, {"Out"});
     }
 

ngraph/test/frontend/paddlepaddle/op_fuzzy.cpp

@@ -202,6 +202,9 @@ static const std::vector<std::string> models{std::string("argmax"),
                                              std::string("sigmoid"),
                                              std::string("slice"),
                                              std::string("slice_1d"),
+                                             std::string("slice_decrease_axis/slice_decrease_axis.pdmodel"),
+                                             std::string("slice_decrease_axis_all/slice_decrease_axis_all.pdmodel"),
+                                             std::string("slice_reshape/slice_reshape.pdmodel"),
                                              std::string("softmax"),
                                              std::string("softmax_minus"),
                                              std::string("split_test1"),

ngraph/test/frontend/paddlepaddle/test_models/gen_scripts/generate_slice.py

@@ -1,10 +1,14 @@
 #
 # slice paddle model generator
 #
-import numpy as np
-from save_model import saveModel
-import paddle as pdpd
 import sys
+import os
+
+import numpy as np
+import paddle as pdpd
+
+from save_model import exportModel
+from save_model import saveModel
 
 data_type = 'float32'
 
@@ -28,6 +32,59 @@ def slice(name : str, x, axes : list, start : list, end : list):
 
     return outs[0]
 
+
+def slice_dyn(test_shape=[2,8,10,10]):
+    pdpd.disable_static()
+
+    data = pdpd.rand(shape=test_shape, dtype='float32')
+
+    '''
+    slice w/ decrease_axis
+    '''
+    @pdpd.jit.to_static
+    def test_slice_decrease_axis(x):
+        return x[0, 1:3, :, 5]
+    exportModel('slice_decrease_axis', test_slice_decrease_axis, [data], target_dir=sys.argv[1]) # output shape (2, 10)
+
+    '''
+    slice w/o decrease_axis
+    '''
+    @pdpd.jit.to_static
+    def test_slice(x):
+        return pdpd.slice(x, axes=[0,1,3], starts=[0,1,5], ends=[1,3,6])
+    # exportModel('slice_dyn', test_slice, [data], target_dir=sys.argv[1]) # output shape (1, 2, 10, 1)  # disable it by default as this kind of test model already there. It's for comparsion only.
+
+    '''
+    slice w/ decrease_axis of all dims
+    '''
+    @pdpd.jit.to_static
+    def test_slice_decrease_axis_all(x):
+        return x[0, 0, 0, 0]
+    exportModel('slice_decrease_axis_all', test_slice_decrease_axis_all, [data], target_dir=sys.argv[1]) # output shape (1,)
+
+    '''
+    slice w/o decrease_axis of all dims
+    '''
+    @pdpd.jit.to_static
+    def test_slice_alldim(x):
+        return pdpd.slice(x, axes=[0,1,2,3], starts=[0,0,0,0], ends=[1,1,1,1])
+    # exportModel('slice_alldim', test_slice_alldim, [data], target_dir=sys.argv[1]) # output shape (1, 1, 1, 1) # disable it by default as this kind of test model already there. It's for comparsion only.
+
+'''
+a test case simulating the last reshape2 of ocrnet which accepts slice (with decrease_axes in all dims) as its parents.
+'''
+def slice_reshape(B=1, C=256, H=16, W=32):
+    pdpd.disable_static()
+
+    data = pdpd.rand(shape=[B, C, H*W], dtype='float32')
+
+    @pdpd.jit.to_static
+    def test_model(x):
+        x2 = pdpd.assign([-1, -1, 16, 32]).astype('int32')
+        node_reshape = pdpd.reshape(x, [0, 256, x2[2], x2[3]])
+        return node_reshape
+    exportModel('slice_reshape', test_model, [data], target_dir=sys.argv[1])
+
 def main():
     x = np.linspace(1, 60, num = 60, dtype=np.int32).reshape(4, 3, 5).astype(data_type)
     slice("slice", x, axes=[1, 2], start=(0, 1), end=(-1, 3))
@@ -36,4 +93,6 @@ def main():
     slice("slice_1d", x, axes=[0], start=[0], end=[1])
 
 if __name__ == "__main__":
-    main()
+    main()
+    slice_dyn()
+    slice_reshape()

ngraph/test/frontend/paddlepaddle/test_models/gen_scripts/save_model.py

@@ -1,4 +1,5 @@
 import os
+import sys
 import numpy as np
 import paddle as pdpd
 
@@ -55,6 +56,42 @@ def saveModel(name, exe, feedkeys:list, fetchlist:list, inputs:list, outputs:lis
     pdpd.fluid.io.save_inference_model(model_dir, feedkeys, fetchlist, exe, model_filename=name+".pdmodel", params_filename=name+".pdiparams")   
 
 
+'''
+export dyn model, along with input and output for reference.
+input_data: list of all inputs
+'''
+def exportModel(name, dyn_func, input_data:list, target_dir:str):
+    model_dir = os.path.join(target_dir, name)
+    if not os.path.exists(model_dir):
+        os.makedirs(model_dir)
+    save_path = '{}/{}'.format(model_dir, name)
+
+    input_specs = []
+    for idx, data in enumerate(input_data):
+        input_name = 'input{}'.format(idx)
+        input_specs.append(
+            pdpd.static.InputSpec(shape=data.shape, dtype=data.dtype, name=input_name)
+        )
+
+        # dump input
+        np.save(os.path.join(model_dir, "input{}".format(idx)), data)        
+
+    pdpd.jit.save(dyn_func, save_path, input_specs)
+    print('saved exported model to {}'.format(save_path))
+
+    # infer
+    model = pdpd.jit.load(save_path)
+
+    result = model(*[input[:] for input in input_data])
+   
+    # dump output for reference
+    if isinstance(result, (tuple, list)):
+        for idx, out in enumerate(result):
+            np.save(os.path.join(model_dir, "output{}".format(idx)), out.numpy())
+    else:       
+        np.save(os.path.join(model_dir, "output{}".format(0)), result.numpy())
+
+
 if __name__ == "__main__":
     np.set_printoptions(precision=2)
     np.set_printoptions(suppress=True)