def test_conversion(self, input_shape, scales, axes):
graph = build_graph(graph_node_attrs,
graph_edges,
{
'placeholder_data': {'shape': int64_array(input_shape)},
'scales': {'value': int64_array(scales), 'shape': int64_array(scales).shape},
'scales_data': {'value': int64_array(scales), 'shape': int64_array(scales).shape},
'upsample_data': {'shape': int64_array(input_shape) * int64_array(scales)}
})
graph.graph['layout'] = 'NCHW'
ref_graph = build_graph(new_ref_graph_node_attr,
new_ref_graph_edges,
{
'placeholder_data': {'shape': int64_array(input_shape)},
'ss_begin': {'value': int64_array([axes[0]])},
'ss_end': {'value': int64_array([axes[-1] + 1])},
'ss_begin_data': {'value': int64_array([axes[0]])},
'ss_end_data': {'value': int64_array([axes[-1] + 1])},
'factor': {'value': int64_array(scales)[2:],
'shape': int64_array(scales[2:]).shape},
'factor_data': {'value': int64_array(scales)[2:],
'shape': int64_array(scales[2:]).shape},
'axes_const': {'value': int64_array(axes), 'shape': int64_array(axes).shape},
'interpolate_data': {'shape': int64_array(input_shape) * int64_array(scales)},
})
UpsampleToResample().find_and_replace_pattern(graph)
(flag, resp) = compare_graphs(graph, ref_graph, 'output')
self.assertTrue(flag, resp)
def test_pattern_does_not_satisfy(self, input_shape, scales):
graph = build_graph(graph_node_attrs, graph_edges,
{'placeholder_data': {'shape': int64_array(input_shape)},
'scales': {'value': int64_array(scales), 'shape': int64_array(scales).shape},
'scales_data': {'value': int64_array(scales), 'shape': int64_array(scales).shape},
'upsample_data': {'shape': int64_array(input_shape) * int64_array(scales)}})
graph.graph['layout'] = 'NCHW'
ref_graph = build_graph(graph_node_attrs, graph_edges,
{'placeholder_data': {'shape': int64_array(input_shape)},
'scales': {'value': int64_array(scales), 'shape': int64_array(scales).shape},
'scales_data': {'value': int64_array(scales), 'shape': int64_array(scales).shape},
'upsample_data': {'shape': int64_array(input_shape) * int64_array(scales)}})
UpsampleToResample().find_and_replace_pattern(graph)
(flag, resp) = compare_graphs(graph, ref_graph, 'output')
self.assertTrue(flag, resp)
def test_conversion(self, input_shape, scales):
graph = build_graph(
graph_node_attrs, graph_edges, {
'placeholder_data': {
'shape': int64_array(input_shape)
},
'scales': {
'value': int64_array(scales),
'shape': int64_array(scales).shape
},
'scales_data': {
'value': int64_array(scales),
'shape': int64_array(scales).shape
},
'upsample_data': {
'shape': int64_array(input_shape) * int64_array(scales)
}
})
graph.graph['layout'] = 'NCHW'
ref_graph = build_graph(
ref_graph_node_attrs, ref_graph_edges, {
'placeholder_data': {
'shape': int64_array(input_shape)
},
'factor': {
'value': int64_array(scales)[2:],
'shape': int64_array(scales[2:]).shape
},
'interpolate_data': {
'shape': int64_array(input_shape) * int64_array(scales)
},
'interpolate': {
'axes': list(range(2, len(input_shape)))
}
})
UpsampleToResample().find_and_replace_pattern(graph)
(flag, resp) = compare_graphs(graph, ref_graph, 'output')
self.assertTrue(flag, resp)