feat/operator_squeeze_unsqueeze

Context

see issue #65 (closed)

aidge_core/unit_tests/test_operator_squeeze.py

+"""
+Copyright (c) 2023 CEA-List
+
+This program and the accompanying materials are made available under the
+terms of the Eclipse Public License 2.0 which is available at
+http://www.eclipse.org/legal/epl-2.0.
+
+SPDX-License-Identifier: EPL-2.0
+"""
+
+import unittest
+import aidge_core
+from aidge_core import Log
+import numpy as np
+from numpy import testing as npt
+
+
+class TestSqueeze(unittest.TestCase):
+    """
+    Test squeeze operator
+    """
+
+    def setUp(self):
+        ############DEFINING INPUT AND OUTPUTS FOR TESTS
+        axes_to_squeeze_0 = [0]
+        axes_to_squeeze_many = [0, 1, 4]
+        axes_to_squeeze_all = []
+        axes_to_squeeze_error = [1, 2, 4, 5, 10, 3, 42, 127, 12, 3, 4, 1, 4, 50]
+
+        squeeze_dim_0 = aidge_core.Squeeze(axes_to_squeeze_0, name="squeeze_dim_0")
+        squeeze_many = aidge_core.Squeeze(axes_to_squeeze_many, name="squeeze_many")
+        squeeze_all = aidge_core.Squeeze(axes_to_squeeze_all, name="squeeze_all")
+        squeeze_error = aidge_core.Squeeze(axes_to_squeeze_error, name="squeeze_error")
+
+        input_1_data_shape = np.array([1, 2, 3])
+        input_2_data_hape = np.array([1, 1, 3, 3, 1, 9])
+        input_3_data_shape = np.array([1])
+        input_4_data_shape = np.array([1, 1, 4])
+
+        input_axes_0 = axes_to_squeeze_0
+        input_axes_many = axes_to_squeeze_many
+        input_axes_all = axes_to_squeeze_all
+        # input_axes_error = aidge_core.Tensor(axes_to_squeeze_error)
+
+        ####################### DEFINING TEST RUNS
+        self.tests_axes_defined_by_attribute = [
+            (input_1_data_shape, squeeze_dim_0, np.array([2, 3])),
+            (input_1_data_shape, squeeze_all, np.array([2, 3])),
+            (input_2_data_hape, squeeze_dim_0, np.array([1, 3, 3, 1, 9])),
+            (input_2_data_hape, squeeze_many, np.array([3, 3, 9])),
+            (input_2_data_hape, squeeze_all, np.array([3, 3, 9])),
+            (input_3_data_shape, squeeze_dim_0, np.array([])),
+            (input_3_data_shape, squeeze_all, np.array([])),
+            (input_4_data_shape, squeeze_dim_0, np.array([1, 4])),
+            (input_4_data_shape, squeeze_all, np.array([4])),
+        ]
+
+        # operators are puprposefully chosen with different predefined attribute than the input_axes tensor
+        self.tests_axes_defined_by_input = [
+            (input_1_data_shape, input_axes_0, squeeze_error, np.array([2, 3])),
+            (input_1_data_shape, input_axes_all, squeeze_error, np.array([2, 3])),
+            (input_2_data_hape, input_axes_0, squeeze_error, np.array([1, 3, 3, 1, 9])),
+            (input_2_data_hape, input_axes_many, squeeze_error, np.array([3, 3, 9])),
+            (input_2_data_hape, input_axes_all, squeeze_error, np.array([3, 3, 9])),
+            (input_3_data_shape, input_axes_0, squeeze_error, np.array([])),
+            (input_3_data_shape, input_axes_all, squeeze_error, np.array([])),
+            (input_4_data_shape, input_axes_0, squeeze_error, np.array([1, 4])),
+            (input_4_data_shape, input_axes_all, squeeze_error, np.array([4])),
+        ]
+        self.test_error = [
+            (input_1_data_shape, squeeze_error),
+            (input_1_data_shape, squeeze_many),
+            (input_3_data_shape, squeeze_many),
+            (input_4_data_shape, squeeze_many),
+        ]
+        return
+
+    def tearDown(self):
+        pass
+
+    def test_axes_defined_via_tensor_input(self):
+        Log.notice("\ntest_axes_defined_via_tensor_input")
+        for index, (
+            input_shape,
+            input_axes_to_squeeze,
+            squeeze_node_template,
+            output_shape,
+        ) in enumerate(self.tests_axes_defined_by_input):
+            test_squeeze_node = squeeze_node_template
+            test_squeeze_op = test_squeeze_node.get_operator()
+
+            print(f"\nTest {index}")
+            print(f"input shape : {input_shape}")
+            print(f"input axes: {np.array(input_axes_to_squeeze)}")
+            print(f"operator : {test_squeeze_node}")
+            print(f"expected output_shape : {output_shape}")
+
+            test_squeeze_op.set_backend("cpu")
+            test_squeeze_op.set_datatype(aidge_core.dtype.float32)
+
+            input_values = np.ones(shape=input_shape, dtype=np.float32)
+            output_values = np.ones(shape=output_shape, dtype=np.float32)
+
+            input_data = aidge_core.Tensor(input_values)
+            input_data.set_datatype(aidge_core.dtype.float32)
+            input_data.set_backend("cpu")
+
+            input_axes = aidge_core.Tensor(
+                np.array(input_axes_to_squeeze, dtype=np.float32)
+            )
+            input_axes.set_datatype(aidge_core.dtype.int8)
+            input_axes.set_backend("cpu")
+
+            test_squeeze_op.set_input(0, input_data)
+            test_squeeze_op.set_input(1, input_axes)
+
+            self.assertEqual(test_squeeze_op.forward_dims(True), True)
+            test_squeeze_op.forward()
+
+            squeeze_output = test_squeeze_op.get_output(0)
+
+            npt.assert_array_equal(
+                squeeze_output.dims(),
+                output_shape,
+                err_msg=f"SQUEEZE FAILURE : expected result differs from output size\n\toperator : {test_squeeze_node}\n\tinput.shape : {input_shape.shape}",
+            )
+            npt.assert_array_almost_equal(
+                np.array(squeeze_output, dtype=np.float32),
+                output_values,
+                7,
+                err_msg=f"SQUEEZE FAILURE : output tensor values differs from expected values\n\toperator : {test_squeeze_node}\n\tinput.shape : {input_shape.shape}",
+            )
+            # self.assertEqual(test_squeeze_op.dims_forwarded(), True, "SQUEEZE_FAILURE : dims_forwarded failed.")
+        return
+
+    def test_axes_defined_via_attribute(self):
+        Log.notice("\ntest_axes_defined_via_attribute")
+        for index, (input_shape, squeeze_node_template, output_shape) in enumerate(
+            self.tests_axes_defined_by_attribute
+        ):
+            test_squeeze_node = squeeze_node_template
+            test_squeeze_op = test_squeeze_node.get_operator()
+
+            print(f"\nTest {index}")
+            print(f"input size : {input_shape.shape}")
+            print(f"operator : {test_squeeze_node}")
+            print(f"expected output_shape : {output_shape}")
+
+            test_squeeze_node.get_operator().set_backend("cpu")
+
+            input_values = np.ones(shape=input_shape, dtype=np.float32)
+            output_values = np.ones(shape=output_shape, dtype=np.float32)
+            input_data = aidge_core.Tensor(input_values)
+            input_data.set_datatype(aidge_core.dtype.float32)
+            input_data.set_backend("cpu")
+            test_squeeze_op.set_input(0, input_data)
+
+            test_squeeze_op.forward_dims()
+            test_squeeze_op.forward()
+
+            squeeze_output = test_squeeze_op.get_output(0)
+
+            npt.assert_array_equal(
+                squeeze_output.dims(),
+                output_shape,
+                err_msg=f"SQUEEZE FAILURE : expected result differs from output size\n\toperator : {test_squeeze_node}\n\tinput.shape : {input_shape.shape}",
+            )
+            npt.assert_array_almost_equal(
+                np.array(squeeze_output, dtype=np.float32),
+                output_values,
+                7,
+                err_msg=f"SQUEEZE FAILURE : output tensor values differs from expected values\n\toperator : {test_squeeze_node}\n\tinput.shape : {input_shape.shape}",
+            )
+        return
+
+    def test_error(self):
+        for input_shape, squeeze_node_template in self.test_error:
+            test_squeeze_node = squeeze_node_template
+            test_squeeze_op = test_squeeze_node.get_operator()
+
+            input_values = np.ones(shape=input_shape)
+            input_data = aidge_core.Tensor(input_values)
+            input_data.set_datatype(aidge_core.dtype.float32)
+            input_data.set_backend("cpu")
+            test_squeeze_op.set_input(0, input_data)
+
+            with self.assertRaises((RuntimeError, AssertionError)):
+                test_squeeze_op.forward_dims()
+                test_squeeze_op.forward()
+        return
+
+
+if __name__ == "__main__":
+    unittest.main()