def tf_matmul_infer(node):
assert (len(node.in_nodes()) == 2)
shapes = [node.in_node(i).shape.copy() for i in range(2)]
log.debug('matmul shapes: {}'.format(shapes))
if any(s is None or len(s) < 2 for s in shapes):
log.error("MatMul wasn't able to infer shape")
return
if node.transpose_a:
perm = np.array(range(len(node.in_node(0).shape)), dtype=np.int64)
perm[-1], perm[-2] = perm[-2], perm[-1]
inv = PermuteAttrs.get_inverse_permutation(perm)
permutation = PermuteAttrs.Permutation(perm=perm, inv=int64_array(inv))
PermuteAttrs.set_permutation(node.in_node(0), node, permutation)
shapes[0] = shapes[0][perm]
if node.transpose_b:
perm = np.array(range(len(node.in_node(1).shape)), dtype=np.int64)
perm[-1], perm[-2] = perm[-2], perm[-1]
inv = PermuteAttrs.get_inverse_permutation(perm)
permutation = PermuteAttrs.Permutation(perm=perm, inv=int64_array(inv))
PermuteAttrs.set_permutation(node.in_node(1), node, permutation)
shapes[1] = shapes[1][perm]
if any(shapes[0][:-2] != shapes[1][:-2]) or shapes[0][-1] != shapes[1][-2]:
log.error(
"MatMul wasn't able to infer shape because input dimensions are not compatible"
)
return
shape_tuple = (np.array(shapes[0][:-1], dtype=np.int64),
np.array([shapes[1][-1]], dtype=np.int64))
if len(shapes[0]) > 2:
# TODO Investigate case when MatMul have inputs with not matching output dimensions
# It looks to be a practical case and if we add outer dimensions of the first argument
# it will lead to incorrect model sometimes. TF documentation is unclear.
log.warning(
'Ignored outer dimensions of input tensor for MatMul node: {}'.
format(node.name))
# shape_tuple = (shapes[0][:-2], *shape_tuple)
log.debug('shape_tuple: {}'.format(shape_tuple))
node.out_node().shape = np.concatenate(shape_tuple)
node['channel_dims'] = node.out_node().shape.size - 1
log.debug('matmul shape: {}'.format(node.out_node().shape))
def reverse_permute(output_shape: np.array, order: np.array):
"""
Calculates Transpose op input shape based on output shape and permute order.
:param output_shape: Transpose output shape
:param order: permute order
:return: Transpose input shape corresponding to the specified output shape
"""
return int64_array(output_shape[PermuteAttrs.get_inverse_permutation(order)])