Supporting negative axes for all existing onnx ops (onnx#2281)

* Added negative axes for slice and squeeze opset 11 * added negative axes support for squeeze, unsqueeze, flatten * added support for negative axes to all the existing ops * fixed minor if condition missed for axis attr in flatten * fixed test name for flatten with negative axes * updated unsqueeze and softmax tests with fix for failures * fixed typo * Updating Split op documentations and version * fixed typo in unsqueeze model * fixed dim check for unsqueeze * fixed type cast * test fix for build failure * updating onnx model for unsqueeze test * fixed minor error in type casting
jcwchen · Sep 10, 2019 · e17df4e · e17df4e
1 parent 81a9503
commit e17df4e
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diff --git a/docs/Changelog.md b/docs/Changelog.md
diff --git a/docs/Operators.md b/docs/Operators.md
diff --git a/docs/TestCoverage.md b/docs/TestCoverage.md
diff --git a/onnx/backend/test/case/node/argmax.py b/onnx/backend/test/case/node/argmax.py
@@ -77,3 +77,23 @@ def export_default_axes_keepdims():  # type: () -> None
         # result's shape: [1, 3, 4]
         result = argmax_use_numpy(data, keepdims=keepdims)
         expect(node, inputs=[data], outputs=[result], name='test_argmax_default_axis_random')
+
+    @staticmethod
+    def export_negative_axis_keepdims():  # type: () -> None
+        data = np.array([[2, 1], [3, 10]], dtype=np.float32)
+        axis = -1
+        keepdims = 1
+        node = onnx.helper.make_node(
+            'ArgMax',
+            inputs=['data'],
+            outputs=['result'],
+            axis=axis,
+            keepdims=keepdims)
+        # result: [[0], [1]]
+        result = argmax_use_numpy(data, axis=axis, keepdims=keepdims)
+        expect(node, inputs=[data], outputs=[result], name='test_argmax_negative_axis_keepdims_example')
+
+        data = np.random.uniform(-10, 10, [2, 3, 4]).astype(np.float32)
+        # result's shape: [2, 3, 1]
+        result = argmax_use_numpy(data, axis=axis, keepdims=keepdims)
+        expect(node, inputs=[data], outputs=[result], name='test_argmax_negative_axis_keepdims_random')
diff --git a/onnx/backend/test/case/node/argmin.py b/onnx/backend/test/case/node/argmin.py
@@ -77,3 +77,23 @@ def export_default_axes_keepdims():  # type: () -> None
         # result's shape: [1, 3, 4]
         result = argmin_use_numpy(data, keepdims=keepdims)
         expect(node, inputs=[data], outputs=[result], name='test_argmin_default_axis_random')
+
+    @staticmethod
+    def export_negative_axis_keepdims():  # type: () -> None
+        data = np.array([[2, 1], [3, 10]], dtype=np.float32)
+        axis = -1
+        keepdims = 1
+        node = onnx.helper.make_node(
+            'ArgMin',
+            inputs=['data'],
+            outputs=['result'],
+            axis=axis,
+            keepdims=keepdims)
+        # result: [[1], [0]]
+        result = argmin_use_numpy(data, axis=axis, keepdims=keepdims)
+        expect(node, inputs=[data], outputs=[result], name='test_argmin_negative_axis_keepdims_example')
+
+        data = np.random.uniform(-10, 10, [2, 3, 4]).astype(np.float32)
+        # result's shape: [2, 3, 1]
+        result = argmin_use_numpy(data, axis=axis, keepdims=keepdims)
+        expect(node, inputs=[data], outputs=[result], name='test_argmin_negative_axis_keepdims_random')
diff --git a/onnx/backend/test/case/node/compress.py b/onnx/backend/test/case/node/compress.py
@@ -64,3 +64,21 @@ def export_compress_default_axis():  # type: () -> None
 
         expect(node, inputs=[input, condition.astype(np.bool)], outputs=[output],
                name='test_compress_default_axis')
+
+    @staticmethod
+    def export_compress_negative_axis():  # type: () -> None
+        node = onnx.helper.make_node(
+            'Compress',
+            inputs=['input', 'condition'],
+            outputs=['output'],
+            axis=-1,
+        )
+        input = np.array([[1, 2], [3, 4], [5, 6]]).astype(np.float32)
+        condition = np.array([0, 1])
+        output = np.compress(condition, input, axis=-1)
+        # print(output)
+        #[[ 2.]
+        # [ 4.]
+        # [ 6.]]
+        expect(node, inputs=[input, condition.astype(np.bool)], outputs=[output],
+               name='test_compress_negative_axis')
diff --git a/onnx/backend/test/case/node/concat.py b/onnx/backend/test/case/node/concat.py
@@ -37,3 +37,15 @@ def export():  # type: () -> None
                 output = np.concatenate(values, i)
                 expect(node, inputs=[v for v in values], outputs=[output],
                        name='test_concat_' + test_case + '_axis_' + str(i))
+
+            for i in range(-len(values[0].shape), 0):
+                in_args = ['value' + str(k) for k in range(len(values))]
+                node = onnx.helper.make_node(
+                    'Concat',
+                    inputs=[s for s in in_args],
+                    outputs=['output'],
+                    axis=i
+                )
+                output = np.concatenate(values, i)
+                expect(node, inputs=[v for v in values], outputs=[output],
+                       name='test_concat_' + test_case + '_axis_negative_' + str(abs(i)))
diff --git a/onnx/backend/test/case/node/cumsum.py b/onnx/backend/test/case/node/cumsum.py
@@ -92,3 +92,16 @@ def export_cumsum_2d_axis_1():  # type: () -> None
         y = np.array([1., 3., 6., 4., 9., 15.]).astype(np.float64).reshape((2, 3))
         expect(node, inputs=[x, axis], outputs=[y],
                name='test_cumsum_2d_axis_1')
+
+    @staticmethod
+    def export_cumsum_2d_negative_axis():  # type: () -> None
+        node = onnx.helper.make_node(
+            'CumSum',
+            inputs=['x', 'axis'],
+            outputs=['y'],
+        )
+        x = np.array([1., 2., 3., 4., 5., 6.]).astype(np.float64).reshape((2, 3))
+        axis = np.array([-1]).astype(np.int32)
+        y = np.array([1., 3., 6., 4., 9., 15.]).astype(np.float64).reshape((2, 3))
+        expect(node, inputs=[x, axis], outputs=[y],
+               name='test_cumsum_2d_negative_axis')
diff --git a/onnx/backend/test/case/node/flatten.py b/onnx/backend/test/case/node/flatten.py
@@ -44,3 +44,21 @@ def export_flatten_with_default_axis():  # type: () -> None
         b = np.reshape(a, new_shape)
         expect(node, inputs=[a], outputs=[b],
                name='test_flatten_default_axis')
+
+    @staticmethod
+    def export_flatten_negative_axis():  # type: () -> None
+        shape = (2, 3, 4, 5)
+        a = np.random.random_sample(shape).astype(np.float32)
+
+        for i in range(-len(shape), 0):
+            node = onnx.helper.make_node(
+                'Flatten',
+                inputs=['a'],
+                outputs=['b'],
+                axis=i,
+            )
+
+            new_shape = (np.prod(shape[0:i]).astype(int), -1)
+            b = np.reshape(a, new_shape)
+            expect(node, inputs=[a], outputs=[b],
+                   name='test_flatten_negative_axis' + str(abs(i)))
diff --git a/onnx/backend/test/case/node/hardmax.py b/onnx/backend/test/case/node/hardmax.py
@@ -75,3 +75,13 @@ def hardmax_2d(x):  # type: (np.ndarray) -> np.ndarray
         y = hardmax_2d(x.reshape(12, 5)).reshape(3, 4, 5)
         expect(node, inputs=[x], outputs=[y],
                name='test_hardmax_axis_2')
+
+        node = onnx.helper.make_node(
+            'Hardmax',
+            inputs=['x'],
+            outputs=['y'],
+            axis=-1,
+        )
+        y = hardmax_2d(x.reshape(12, 5)).reshape(3, 4, 5)
+        expect(node, inputs=[x], outputs=[y],
+               name='test_hardmax_negative_axis')
diff --git a/onnx/backend/test/case/node/logsoftmax.py b/onnx/backend/test/case/node/logsoftmax.py
@@ -84,3 +84,13 @@ def logsoftmax_2d(x):  # type: (np.ndarray) -> np.ndarray
         y = logsoftmax_2d(x.reshape(12, 5)).reshape(3, 4, 5)
         expect(node, inputs=[x], outputs=[y],
                name='test_logsoftmax_axis_2')
+
+        node = onnx.helper.make_node(
+            'LogSoftmax',
+            inputs=['x'],
+            outputs=['y'],
+            axis=-1,
+        )
+        y = logsoftmax_2d(x.reshape(12, 5)).reshape(3, 4, 5)
+        expect(node, inputs=[x], outputs=[y],
+               name='test_logsoftmax_negative_axis')
diff --git a/onnx/backend/test/case/node/onehot.py b/onnx/backend/test/case/node/onehot.py
@@ -62,3 +62,23 @@ def export_with_axis():  # type: () -> None
         y = one_hot(indices, depth, axis=axisValue, dtype=output_type)
         y = y * (on_value - off_value) + off_value
         expect(node, inputs=[indices, depth, values], outputs=[y], name='test_onehot_with_axis')
+
+    @staticmethod
+    def export_with_negative_axis():  # type: () -> None
+        axisValue = -2
+        on_value = 3
+        off_value = 1
+        output_type = np.float32
+        node = onnx.helper.make_node(
+            'OneHot',
+            inputs=['indices', 'depth', 'values'],
+            outputs=['y'],
+            axis=axisValue
+        )
+        indices = np.array([[1, 9],
+                            [2, 4]], dtype=np.float32)
+        depth = np.array([10], dtype=np.float32)
+        values = np.array([off_value, on_value], dtype=output_type)
+        y = one_hot(indices, depth, axis=axisValue, dtype=output_type)
+        y = y * (on_value - off_value) + off_value
+        expect(node, inputs=[indices, depth, values], outputs=[y], name='test_onehot_with_negative_axis')
diff --git a/onnx/backend/test/case/node/reduce_log_sum.py b/onnx/backend/test/case/node/reduce_log_sum.py
@@ -49,3 +49,17 @@ def export_keepdims():  # type: () -> None
         reduced = np.log(np.sum(data, keepdims=True))
         expect(node, inputs=[data], outputs=[reduced],
                name='test_reduce_log_sum_default')
+
+    @staticmethod
+    def export_negative_axes_keepdims():  # type: () -> None
+        node = onnx.helper.make_node(
+            'ReduceLogSum',
+            inputs=['data'],
+            outputs=["reduced"],
+            axes=[-2]
+        )
+        data = np.random.ranf([3, 4, 5]).astype(np.float32)
+        reduced = np.log(np.sum(data, axis=(-2), keepdims=True))
+        # print(reduced)
+        expect(node, inputs=[data], outputs=[reduced],
+               name='test_reduce_log_sum_negative_axes')
diff --git a/...backend/test/case/node/reducelogsumexp.py → ...kend/test/case/node/reduce_log_sum_exp.py b/...backend/test/case/node/reducelogsumexp.py → ...kend/test/case/node/reduce_log_sum_exp.py
@@ -114,3 +114,39 @@ def export_default_axes_keepdims():  # type: () -> None
                                 keepdims=keepdims == 1))
         expect(node, inputs=[data], outputs=[reduced],
               name='test_reduce_log_sum_exp_default_axes_keepdims_random')
+
+    @staticmethod
+    def export_negative_axes_keepdims():  # type: () -> None
+        shape = [3, 2, 2]
+        axes = [-2]
+        keepdims = 1
+        node = onnx.helper.make_node(
+            'ReduceLogSumExp',
+            inputs=['data'],
+            outputs=['reduced'],
+            axes=axes,
+            keepdims=keepdims
+        )
+
+        data = np.array(
+            [[[5, 1], [20, 2]], [[30, 1], [40, 2]], [[55, 1], [60, 2]]],
+            dtype=np.float32)
+        reduced = np.log(np.sum(np.exp(data),
+                                axis=tuple(axes),
+                                keepdims=keepdims == 1))
+        # print(reduced)
+        # [[[20., 2.31326175]]
+        # [[40.00004578, 2.31326175]]
+        # [[60.00671387, 2.31326175]]]
+
+        expect(node, inputs=[data], outputs=[reduced],
+              name='test_reduce_log_sum_exp_negative_axes_keepdims_example')
+
+        np.random.seed(0)
+        data = np.random.uniform(-10, 10, shape).astype(np.float32)
+        reduced = np.log(np.sum(np.exp(data),
+                                axis=tuple(axes),
+                                keepdims=keepdims == 1))
+
+        expect(node, inputs=[data], outputs=[reduced],
+              name='test_reduce_log_sum_exp_negative_axes_keepdims_random')
diff --git a/onnx/backend/test/case/node/reducel1.py b/onnx/backend/test/case/node/reducel1.py
@@ -106,3 +106,35 @@ def export_default_axes_keepdims():  # type: () -> None
 
         expect(node, inputs=[data], outputs=[reduced],
             name='test_reduce_l1_default_axes_keepdims_random')
+
+    @staticmethod
+    def export_negative_axes_keepdims():  # type: () -> None
+        shape = [3, 2, 2]
+        axes = [-1]
+        keepdims = 1
+
+        node = onnx.helper.make_node(
+            'ReduceL1',
+            inputs=['data'],
+            outputs=['reduced'],
+            axes=axes,
+            keepdims=keepdims
+        )
+
+        data = np.reshape(np.arange(1, np.prod(shape) + 1, dtype=np.float32), shape)
+        # print(data)
+        #[[[1., 2.], [3., 4.]], [[5., 6.], [7., 8.]], [[9., 10.], [11., 12.]]]
+
+        reduced = np.sum(a=np.abs(data), axis=tuple(axes), keepdims=keepdims == 1)
+        # print(reduced)
+        #[[[3.], [7.]], [[11.], [15.]], [[19.], [23.]]]
+
+        expect(node, inputs=[data], outputs=[reduced],
+            name='test_reduce_l1_negative_axes_keep_dims_example')
+
+        np.random.seed(0)
+        data = np.random.uniform(-10, 10, shape).astype(np.float32)
+        reduced = np.sum(a=np.abs(data), axis=tuple(axes), keepdims=keepdims == 1)
+
+        expect(node, inputs=[data], outputs=[reduced],
+            name='test_reduce_l1_negative_axes_keep_dims_random')
diff --git a/onnx/backend/test/case/node/reducel2.py b/onnx/backend/test/case/node/reducel2.py
@@ -115,3 +115,39 @@ def export_default_axes_keepdims():  # type: () -> None
 
         expect(node, inputs=[data], outputs=[reduced],
             name='test_reduce_l2_default_axes_keepdims_random')
+
+    @staticmethod
+    def export_negative_axes_keepdims():  # type: () -> None
+        shape = [3, 2, 2]
+        axes = [-1]
+        keepdims = 1
+
+        node = onnx.helper.make_node(
+            'ReduceL2',
+            inputs=['data'],
+            outputs=['reduced'],
+            axes=axes,
+            keepdims=keepdims
+        )
+
+        data = np.reshape(np.arange(1, np.prod(shape) + 1, dtype=np.float32), shape)
+        # print(data)
+        #[[[1., 2.], [3., 4.]], [[5., 6.], [7., 8.]], [[9., 10.], [11., 12.]]]
+
+        reduced = np.sqrt(np.sum(
+            a=np.square(data), axis=tuple(axes), keepdims=keepdims == 1))
+        # print(reduced)
+        #[[[2.23606798], [5.]]
+        # [[7.81024968], [10.63014581]]
+        # [[13.45362405], [16.2788206 ]]]
+
+        expect(node, inputs=[data], outputs=[reduced],
+            name='test_reduce_l2_negative_axes_keep_dims_example')
+
+        np.random.seed(0)
+        data = np.random.uniform(-10, 10, shape).astype(np.float32)
+        reduced = np.sqrt(np.sum(
+            a=np.square(data), axis=tuple(axes), keepdims=keepdims == 1))
+
+        expect(node, inputs=[data], outputs=[reduced],
+            name='test_reduce_l2_negative_axes_keep_dims_random')
diff --git a/onnx/backend/test/case/node/reducemax.py b/onnx/backend/test/case/node/reducemax.py
@@ -91,3 +91,31 @@ def export_default_axes_keepdims():  # type: () -> None
         reduced = np.maximum.reduce(data, axis=axes, keepdims=keepdims == 1)
 
         expect(node, inputs=[data], outputs=[reduced], name='test_reduce_max_default_axes_keepdims_random')
+
+    @staticmethod
+    def export_negative_axes_keepdims():  # type: () -> None
+        shape = [3, 2, 2]
+        axes = [-2]
+        keepdims = 1
+
+        node = onnx.helper.make_node(
+            'ReduceMax',
+            inputs=['data'],
+            outputs=['reduced'],
+            axes=axes,
+            keepdims=keepdims)
+
+        data = np.array([[[5, 1], [20, 2]], [[30, 1], [40, 2]], [[55, 1], [60, 2]]], dtype=np.float32)
+        reduced = np.maximum.reduce(data, axis=tuple(axes), keepdims=keepdims == 1)
+        # print(reduced)
+        #[[[20., 2.]]
+        # [[40., 2.]]
+        # [[60., 2.]]]
+
+        expect(node, inputs=[data], outputs=[reduced], name='test_reduce_max_negative_axes_keepdims_example')
+
+        np.random.seed(0)
+        data = np.random.uniform(-10, 10, shape).astype(np.float32)
+        reduced = np.maximum.reduce(data, axis=tuple(axes), keepdims=keepdims == 1)
+
+        expect(node, inputs=[data], outputs=[reduced], name='test_reduce_max_negative_axes_keepdims_random')
diff --git a/onnx/backend/test/case/node/reducemean.py b/onnx/backend/test/case/node/reducemean.py
@@ -92,3 +92,31 @@ def export_default_axes_keepdims():  # type: () -> None
         reduced = np.mean(data, axis=axes, keepdims=keepdims == 1)
 
         expect(node, inputs=[data], outputs=[reduced], name='test_reduce_mean_default_axes_keepdims_random')
+
+    @staticmethod
+    def export_negative_axes_keepdims():  # type: () -> None
+        shape = [3, 2, 2]
+        axes = [-2]
+        keepdims = 1
+
+        node = onnx.helper.make_node(
+            'ReduceMean',
+            inputs=['data'],
+            outputs=['reduced'],
+            axes=axes,
+            keepdims=keepdims)
+
+        data = np.array([[[5, 1], [20, 2]], [[30, 1], [40, 2]], [[55, 1], [60, 2]]], dtype=np.float32)
+        reduced = np.mean(data, axis=tuple(axes), keepdims=keepdims == 1)
+        # print(reduced)
+        # [[[12.5, 1.5]]
+        # [[35., 1.5]]
+        # [[57.5, 1.5]]]
+
+        expect(node, inputs=[data], outputs=[reduced], name='test_reduce_mean_negative_axes_keepdims_example')
+
+        np.random.seed(0)
+        data = np.random.uniform(-10, 10, shape).astype(np.float32)
+        reduced = np.mean(data, axis=tuple(axes), keepdims=keepdims == 1)
+
+        expect(node, inputs=[data], outputs=[reduced], name='test_reduce_mean_negative_axes_keepdims_random')