[cherry-pick ] add input type and dtype check for squeeze (#20100) (#20446)

* Add input check and refine error message

* Refine test case and comments

test=develop
Signed-off-by: Nzhaoyuchen <zhaoyuchen01@baidu.com>

paddle/fluid/operators/squeeze_op.cc

@@ -35,14 +35,19 @@ class SqueezeOp : public framework::OperatorWithKernel {
     const auto &x_dims = ctx->GetInputDim("X");
     // Check input tensor dims (<6) Eigen limit.
     PADDLE_ENFORCE_LE(x_dims.size(), 6,
-                      "Invalid dimnesions, the rank of Input(X) "
-                      "should be in the range of [1, 6] (Eigen limit).");
+                      "ShapeError: the dimensions of Input(X) "
+                      "should be in the range of [1, 6] (Eigen limit)."
+                      "But received X's dimensions = %d, X's shape=[%s].",
+                      x_dims.size(), x_dims);
 
     const auto &axes = ctx->Attrs().Get<std::vector<int>>("axes");
     for (int a : axes) {
-      PADDLE_ENFORCE_LT(a, x_dims.size(),
-                        "The squeeze axis should be less than input "
-                        "tensor's rank.");
+      PADDLE_ENFORCE_LT(
+          a, x_dims.size(),
+          "ShapeError: The squeeze axis should be less than input "
+          "tensor's dimensions. But received axis = %d, input "
+          "tensor's dimensions = %d, input tensor's shape = [%s].",
+          a, x_dims.size(), x_dims);
     }
 
     auto out_dims = GetOutputShape(axes, x_dims);
@@ -73,9 +78,10 @@ class SqueezeOp : public framework::OperatorWithKernel {
       for (size_t idx = 0; idx < num_squeeze_dims; ++idx) {
         int current = squeeze_dims[idx] < 0 ? squeeze_dims[idx] + in_dims.size()
                                             : squeeze_dims[idx];
-        // Check current index, the upper limit has beed checked in line 36.
         PADDLE_ENFORCE_GE(current, 0,
-                          "Invalid axis, the negative axis is out of range.");
+                          "Invalid axis, the axis should >= 0."
+                          "Current axis is:%d, input tensor's shape = [%s].",
+                          current, in_dims);
 
         if (!(should_squeeze[current])) {
           ++cnt_squeezed_dims;
@@ -171,14 +177,19 @@ class Squeeze2Op : public framework::OperatorWithKernel {
     const auto &x_dims = ctx->GetInputDim("X");
     // Check input tensor dims (<6) Eigen limit.
     PADDLE_ENFORCE_LE(x_dims.size(), 6,
-                      "Invalid dimnesions, the rank of Input(X) "
-                      "should be in the range of [1, 6] (Eigen limit).");
+                      "ShapeError: the dimensions of Input(X) "
+                      "should be in the range of [1, 6] (Eigen limit)."
+                      "But received X's dimensions = %d, X's shape = [%s].",
+                      x_dims.size(), x_dims);
 
     const auto &axes = ctx->Attrs().Get<std::vector<int>>("axes");
     for (int a : axes) {
-      PADDLE_ENFORCE_LT(a, x_dims.size(),
-                        "The squeeze axis should be less than input "
-                        "tensor's rank.");
+      PADDLE_ENFORCE_LT(
+          a, x_dims.size(),
+          "ShapeError: The squeeze axis should be less than input "
+          "tensor's dimensions. But received axis = %d, input "
+          "tensor's dimensions = %d, input tensor's shape = [%s].",
+          a, x_dims.size(), x_dims);
     }
 
     auto out_dims = SqueezeOp::GetOutputShape(axes, x_dims);

paddle/fluid/operators/squeeze_op.h

@@ -61,13 +61,17 @@ class SqueezeKernel : public framework::OpKernel<T> {
       for (size_t idx = 0; idx < num_squeeze_dims; ++idx) {
         int current = squeeze_dims[idx] < 0 ? squeeze_dims[idx] + in_dims.size()
                                             : squeeze_dims[idx];
-        // Check current index, the upper limit has beed checked in line 36.
+
         PADDLE_ENFORCE_GE(current, 0,
-                          "Invalid axis, the negative axis is out of range.");
+                          "Invalid axis, the axis should >= 0."
+                          "Current axis is:%d, input tensor's shape = [%s].",
+                          current, in_dims);
 
         PADDLE_ENFORCE_EQ(in_dims[current], 1,
                           "Invalid axis index, the axis that will be squeezed "
-                          "should be equal to 1.");
+                          "should be equal to 1. But current axis = %d,"
+                          "input tensor's shape = [%s].",
+                          in_dims[current], in_dims);
 
         if (!(should_squeeze[current])) {
           ++cnt_squeezed_dims;

python/paddle/fluid/layers/nn.py

@@ -8743,6 +8743,23 @@ def squeeze(input, axes, name=None):
     assert not in_dygraph_mode(), (
         "squeeze layer is not supported in dygraph mode yet.")
     helper = LayerHelper("squeeze", **locals())
+
+    if not isinstance(input, Variable):
+        raise TypeError(
+            "The type of 'input' in squeeze must be Variable, but received %s" %
+            (type(input)))
+
+    if convert_dtype(input.dtype
+                     ) not in ['float32', 'float64', 'int8', 'int32', 'int64']:
+        raise TypeError(
+            "The data type of 'input' in squeeze must be float32, float64, int8, int32,"
+            "int64, but received %s." % (convert_dtype(input.dtype)))
+
+    if not isinstance(axes, list):
+        raise TypeError(
+            "The type of 'axes' in squeeze must be list, but received %s" %
+            (type(axes)))
+
     out = helper.create_variable_for_type_inference(dtype=input.dtype)
     x_shape = helper.create_variable_for_type_inference(dtype=input.dtype)
     helper.append_op(

python/paddle/fluid/tests/unittests/test_squeeze_op.py

@@ -16,6 +16,8 @@ from __future__ import print_function
 
 import unittest
 import numpy as np
+import paddle.fluid as fluid
+from paddle.fluid import compiler, Program, program_guard
 
 from op_test import OpTest
 
@@ -68,5 +70,20 @@ class TestSqueezeOp3(TestSqueezeOp):
         self.new_shape = (3, 5, 1, 4)
 
 
+class TestSqueezeOpError(OpTest):
+    def test_errors(self):
+        with program_guard(Program(), Program()):
+            # The input type of softmax_op must be Variable.
+            x1 = fluid.create_lod_tensor(
+                np.array([[-1]]), [[1]], fluid.CPUPlace())
+            self.assertRaises(TypeError, fluid.layers.squeeze, x1)
+            # The input axes of squeeze must be list.
+            x2 = fluid.layers.data(name='x2', shape=[4], dtype="int32")
+            self.assertRaises(TypeError, fluid.layers.squeeze, x2, axes=0)
+            # The input dtype of squeeze not support float16.
+            x3 = fluid.layers.data(name='x3', shape=[4], dtype="float16")
+            self.assertRaises(TypeError, fluid.layers.squeeze, x3, axes=0)
+
+
 if __name__ == "__main__":
     unittest.main()