def array_infer(node: Node):
assert len(node.in_nodes()) == 4
handle = node.in_node(0)
index = node.in_node(1)
value = node.in_node(2)
flow_in = node.in_node(3)
value_shape = value.shape
ta_node = Node(node.graph, str(handle.value))
if ta_node.has_valid('element_shape') and len(
ta_node.element_shape) > 0:
assert match_shapes(ta_node['element_shape'], value.shape), \
'Shapes are not compatible: {} and {}'.format(ta_node['element_shape'], value.shape)
ta_node['element_shape'] = value_shape
output_shape = flow_in.shape
output_value = flow_in.value
# flow_out
for _, out_node in node.graph.out_edges(node.id):
node.graph.node[out_node]['shape'] = np.array(output_shape)
node.graph.node[out_node][
'value'] = None if output_value is None else np.array(
output_value)
def array_infer(node: Node):
handle = node.in_node(0)
indices = node.in_node(1)
value = node.in_node(2)
flow_in = node.in_node(3)
ta_node = Node(node.graph, str(handle.value))
if ta_node.has_valid('element_shape') and len(
ta_node.element_shape) > 0:
assert match_shapes(ta_node['element_shape'], value.shape[1:]), \
'Shapes are not compatible: {} and {}'.format(ta_node['element_shape'], value.shape[1:])
else:
ta_node['element_shape'] = value.shape[1:]
# Assign element_shape anyway, because the original element_shape can contain -1
ta_node['element_shape'] = value.shape[1:]
output_shape = flow_in.shape
output_value = flow_in.value
#flow_out
for _, out_node in node.graph.out_edges(node.id):
node.graph.node[out_node]['shape'] = np.array(output_shape)
node.graph.node[out_node][
'value'] = None if output_value is None else np.array(
output_value)
def run_match_shapes(self, pattern: list, shape: list):
return match_shapes(shape_array(pattern), shape_array(shape))
def run_match_shapes(self, pattern: list, shape: list):
return match_shapes(np.array(pattern, dtype=np.int64),
np.array(shape, dtype=np.int64))