Tensorflow matmul how to deal with channel=None
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I am trying to do matmul of two tensors, one is [None, 4, 256], and the other is its transpose (I use tf.transpose and got a tensor [256, 4, None]). The expected result is a [4, 4] tensor. When I use matmul, it returns an error. I am wondering, how can I get the expected result? Thank you!
#inputs: [None, 4, 256]
inputs_transpose = tf.transpose(inputs, perm = [0, 2, 1]) #[None, 256, 4]
temp_weights = tf.matmul(inputs, inputs_transpose) #[4, 4]expected
python tensorflow matrix-multiplication tensor
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I am trying to do matmul of two tensors, one is [None, 4, 256], and the other is its transpose (I use tf.transpose and got a tensor [256, 4, None]). The expected result is a [4, 4] tensor. When I use matmul, it returns an error. I am wondering, how can I get the expected result? Thank you!
#inputs: [None, 4, 256]
inputs_transpose = tf.transpose(inputs, perm = [0, 2, 1]) #[None, 256, 4]
temp_weights = tf.matmul(inputs, inputs_transpose) #[4, 4]expected
python tensorflow matrix-multiplication tensor
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
I am trying to do matmul of two tensors, one is [None, 4, 256], and the other is its transpose (I use tf.transpose and got a tensor [256, 4, None]). The expected result is a [4, 4] tensor. When I use matmul, it returns an error. I am wondering, how can I get the expected result? Thank you!
#inputs: [None, 4, 256]
inputs_transpose = tf.transpose(inputs, perm = [0, 2, 1]) #[None, 256, 4]
temp_weights = tf.matmul(inputs, inputs_transpose) #[4, 4]expected
python tensorflow matrix-multiplication tensor
I am trying to do matmul of two tensors, one is [None, 4, 256], and the other is its transpose (I use tf.transpose and got a tensor [256, 4, None]). The expected result is a [4, 4] tensor. When I use matmul, it returns an error. I am wondering, how can I get the expected result? Thank you!
#inputs: [None, 4, 256]
inputs_transpose = tf.transpose(inputs, perm = [0, 2, 1]) #[None, 256, 4]
temp_weights = tf.matmul(inputs, inputs_transpose) #[4, 4]expected
python tensorflow matrix-multiplication tensor
python tensorflow matrix-multiplication tensor
edited Nov 10 at 9:45
asked Nov 10 at 9:25
Cindy
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From Tensowflow docs
"Note: This function diverges from default Numpy behavior for float and string types when None is present in a Python list or scalar. Rather than silently converting None values, an error will be thrown."
Tensowflow does not accept None values while creating tensors.
I tried to recreate the setup you had on my system and got this error message:
TypeError: Failed to convert object of type <class 'list'> to Tensor. Contents: [None, 4, 256]. Consider casting elements to a supported type.
You would need to explicitly handle the None by replacing it with a 0 before attempting to use the python list.
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1 Answer
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1 Answer
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active
oldest
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active
oldest
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active
oldest
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up vote
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down vote
From Tensowflow docs
"Note: This function diverges from default Numpy behavior for float and string types when None is present in a Python list or scalar. Rather than silently converting None values, an error will be thrown."
Tensowflow does not accept None values while creating tensors.
I tried to recreate the setup you had on my system and got this error message:
TypeError: Failed to convert object of type <class 'list'> to Tensor. Contents: [None, 4, 256]. Consider casting elements to a supported type.
You would need to explicitly handle the None by replacing it with a 0 before attempting to use the python list.
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up vote
0
down vote
From Tensowflow docs
"Note: This function diverges from default Numpy behavior for float and string types when None is present in a Python list or scalar. Rather than silently converting None values, an error will be thrown."
Tensowflow does not accept None values while creating tensors.
I tried to recreate the setup you had on my system and got this error message:
TypeError: Failed to convert object of type <class 'list'> to Tensor. Contents: [None, 4, 256]. Consider casting elements to a supported type.
You would need to explicitly handle the None by replacing it with a 0 before attempting to use the python list.
add a comment |
up vote
0
down vote
up vote
0
down vote
From Tensowflow docs
"Note: This function diverges from default Numpy behavior for float and string types when None is present in a Python list or scalar. Rather than silently converting None values, an error will be thrown."
Tensowflow does not accept None values while creating tensors.
I tried to recreate the setup you had on my system and got this error message:
TypeError: Failed to convert object of type <class 'list'> to Tensor. Contents: [None, 4, 256]. Consider casting elements to a supported type.
You would need to explicitly handle the None by replacing it with a 0 before attempting to use the python list.
From Tensowflow docs
"Note: This function diverges from default Numpy behavior for float and string types when None is present in a Python list or scalar. Rather than silently converting None values, an error will be thrown."
Tensowflow does not accept None values while creating tensors.
I tried to recreate the setup you had on my system and got this error message:
TypeError: Failed to convert object of type <class 'list'> to Tensor. Contents: [None, 4, 256]. Consider casting elements to a supported type.
You would need to explicitly handle the None by replacing it with a 0 before attempting to use the python list.
answered Nov 10 at 10:42
Paritosh Singh
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