def infer(node: Node):
assert node.has_valid(
'dst_type'
), 'Destination type of "Cast" operation should be extracted earlier'
dst_type = node.dst_type
copy_shape_infer(node)
if node.has_and_set('stop_value_propagation'):
return
if node.in_node(0).has_valid('value'):
new_blob, finite_match_count, zero_match_count = convert_blob(
node.in_node(0).value, dst_type)
node.out_port(0).data.set_value(new_blob)
if finite_match_count:
log.error((
"{} elements of {} were clipped to infinity while converting an input blob for node '{}' to {}. "
+ refer_to_faq_msg(76)).format(finite_match_count,
new_blob.size, node.name,
dst_type))
if zero_match_count:
log.warning((
"{} elements of {} were clipped to zero while converting an input blob for node '{}' to {}. "
+ refer_to_faq_msg(77)).format(zero_match_count,
new_blob.size, node.name,
dst_type))
def helper_value_propagation(node_name, value, dst_type):
new_blob, finite_match_count, zero_match_count = convert_blob(value, dst_type)
if finite_match_count:
log.error("{} elements of {} were clipped to infinity while converting an input blob for node '{}' to {}."
" ".format(finite_match_count, new_blob.size, node_name, dst_type) + refer_to_faq_msg(76))
if zero_match_count:
log.warning("{} elements of {} were clipped to zero while converting an input blob for node '{}' to {}."
" ".format(zero_match_count, new_blob.size, node_name, dst_type) + refer_to_faq_msg(77))
return new_blob
def add_removed_converts(graph: Graph):
for data_node_name in graph.get_nodes_with_attributes(Insert_Convert_operation_after=True):
data_node = Node(graph, data_node_name)
# Get access to Const node connected to data node
const_op = data_node.in_node(0)
assert const_op.data_type == np.float32, "Error when try to insert Convert operation after Const: {}".\
format(const_op.soft_get('name'))
convert_op = Cast(graph, {'dst_type': np.float32,
'name': const_op.name + '/restored_convert',
'stop_value_propagation': True}).create_node()
# Insert Convert operation after Const operation
consumer_port = const_op.out_port(0).get_connection().get_destination()
const_op.out_port(0).get_connection().set_destination(convert_op.in_port(0))
convert_op.out_port(0).connect(consumer_port)
# Convert Const value to FP32 to make types in graph consistent
const_op.value, _, _ = convert_blob(const_op.value, np.float16)
const_op.infer(const_op)