This:
import numpy as np
a = np.array([1, 2, 1])
w = np.array([[.5, .6], [.7, .8], [.7, .8]])
print(np.dot(a, w))
# [ 2.6 3. ] # plain nice old matrix multiplication n x (n, m) -> m
import tensorflow as tf
a = tf.constant(a, dtype=tf.float64)
w = tf.constant(w)
with tf.Session() as sess:
print(tf.matmul(a, w).eval())
results in:
C:\_\Python35\python.exe C:/Users/MrD/.PyCharm2017.1/config/scratches/scratch_31.py
[ 2.6 3. ]
# bunch of errors in windows...
Traceback (most recent call last):
File "C:\_\Python35\lib\site-packages\tensorflow\python\framework\common_shapes.py", line 671, in _call_cpp_shape_fn_impl
input_tensors_as_shapes, status)
File "C:\_\Python35\lib\contextlib.py", line 66, in __exit__
next(self.gen)
File "C:\_\Python35\lib\site-packages\tensorflow\python\framework\errors_impl.py", line 466, in raise_exception_on_not_ok_status
pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors_impl.InvalidArgumentError: Shape must be rank 2 but is rank 1 for 'MatMul' (op: 'MatMul') with input shapes: [3], [3,2].
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:/Users/MrD/.PyCharm2017.1/config/scratches/scratch_31.py", line 14, in <module>
print(tf.matmul(a, w).eval())
File "C:\_\Python35\lib\site-packages\tensorflow\python\ops\math_ops.py", line 1765, in matmul
a, b, transpose_a=transpose_a, transpose_b=transpose_b, name=name)
File "C:\_\Python35\lib\site-packages\tensorflow\python\ops\gen_math_ops.py", line 1454, in _mat_mul
transpose_b=transpose_b, name=name)
File "C:\_\Python35\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 763, in apply_op
op_def=op_def)
File "C:\_\Python35\lib\site-packages\tensorflow\python\framework\ops.py", line 2329, in create_op
set_shapes_for_outputs(ret)
File "C:\_\Python35\lib\site-packages\tensorflow\python\framework\ops.py", line 1717, in set_shapes_for_outputs
shapes = shape_func(op)
File "C:\_\Python35\lib\site-packages\tensorflow\python\framework\ops.py", line 1667, in call_with_requiring
return call_cpp_shape_fn(op, require_shape_fn=True)
File "C:\_\Python35\lib\site-packages\tensorflow\python\framework\common_shapes.py", line 610, in call_cpp_shape_fn
debug_python_shape_fn, require_shape_fn)
File "C:\_\Python35\lib\site-packages\tensorflow\python\framework\common_shapes.py", line 676, in _call_cpp_shape_fn_impl
raise ValueError(err.message)
ValueError: Shape must be rank 2 but is rank 1 for 'MatMul' (op: 'MatMul') with input shapes: [3], [3,2].
Process finished with exit code 1
(not sure why the same exception is raised inside its handling)
The solution suggested in Tensorflow exception with matmul is reshaping the vector to a matrix but this leads to needlessly complicated code - is there still no other way to multiply a vector with a matrix?
Incidentally using expand_dims
(as suggested in the link above) with default arguments raises a ValueError
- that's not mentioned in the docs and defeats the purpose of having a default argument.
You can use tf.tensordot
and set axes=1
. For the simple operation of a vector times a matrix, this is a bit cleaner than tf.einsum
tf.tensordot(a, w, 1)
If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
Donate Us With