def test_infer5(self):
graph = build_graph(nodes_attributes, edges, inputs5)
gathernd_node = Node(graph, 'gathernd_node')
GatherND.infer(gathernd_node)
# get the result
res_output_value = graph.node['output']['value']
self.assertTrue(np.array_equal(output5, res_output_value),
'values do not match expected: {} and given: {}'.format(output4, res_output_value))
def test_partial_infer_gather_slice(self):
graph = build_graph(nodes_attributes, edges, inputs2)
gathernd_node = Node(graph, 'gathernd_node')
GatherND.infer(gathernd_node)
# prepare reference results
ref_output_shape = int64_array([3, 30])
# get the result
res_output_shape = graph.node['output']['shape']
self.assertTrue(np.array_equal(ref_output_shape, res_output_shape),
'values do not match expected: {} and given: {}'.format(ref_output_shape, res_output_shape))
def test_infer9_opset_5(self):
nodes_attributes['gathernd_node']['batch_dims'] = 2
graph = build_graph(nodes_attributes, edges, inputs8)
gathernd_node = Node(graph, 'gathernd_node')
GatherND.infer(gathernd_node)
# get the result
res_output_value = graph.node['output']['value']
output = output8.reshape([6, 3])
self.assertTrue(
np.array_equal(output, res_output_value),
'values do not match expected: {} and given: {}'.format(
output, res_output_value))
def test_partial_infer_gather_slice_batch_dims2_dynamic3(self):
nodes_attributes['gathernd_node']['batch_dims'] = 2
graph = build_graph(nodes_attributes, edges, inputs11)
gathernd_node = Node(graph, 'gathernd_node')
GatherND.infer(gathernd_node)
# prepare reference results
ref_output_shape = shape_array([dynamic_dimension_value, 3, 5, 9])
# get the result
res_output_shape = graph.node['output']['shape']
self.assertTrue(
strict_compare_tensors(ref_output_shape, res_output_shape),
'values do not match expected: {} and given: {}'.format(
ref_output_shape, res_output_shape))
def test_partial_infer_gather_slice_batch_dims3_opset8(self):
nodes_attributes['gathernd_node']['batch_dims'] = 3
nodes_attributes['gathernd_node']['version'] = 'opset8'
graph = build_graph(nodes_attributes, edges, inputs3)
gathernd_node = Node(graph, 'gathernd_node')
GatherND.infer(gathernd_node)
# prepare reference results
ref_output_shape = int64_array([1, 64, 64, 1])
# get the result
res_output_shape = graph.node['output']['shape']
self.assertTrue(
np.array_equal(ref_output_shape, res_output_shape),
'values do not match expected: {} and given: {}'.format(
ref_output_shape, res_output_shape))
def extract(cls, node):
attrs = {'batch_dims': onnx_attr(node, 'batch_dims', 'i', default=0)}
GatherND.update_node_stat(node, attrs)
return cls.enabled
def extract(cls, node):
attrs = {
'batch_dims': 0,
}
GatherND.update_node_stat(node, attrs)
return cls.enabled
