Comments (1)
The final concatenation that merges different windows is what you referred to as parallel. That is what I have implemented.
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Related Issues (20)
- Consistency with the article (HATT) HOT 5
- Tokenization performed with validation data (HATT) HOT 1
- y_permute_dim.pop(-2) pop index out of range HOT 5
- mask zero and activation in HATT HOT 6
- some problem about data preprocess HOT 5
- save model error HOT 3
- Not able to train HAN because of the following error. HOT 8
- AttributeError: 'DataFrame' object has no attribute 'review' HOT 3
- the run problem in textClassifierHATT
- Capturing attention weights and seeing which words contributed to the classification HOT 1
- Dimensions must be equal, but are 15 and 100 for 'att_layer_2/mul' (op: 'Mul') with input shapes: [?,15], [?,15,100]. HOT 12
- Int to long
- ValueError: Error when checking target: expected dense_1 to have 2 dimensions, but got array with shape (40261, 2, 2) HOT 1
- The performance is worse
- ValueError HOT 1
- Incorporating this model into tensorflow project HOT 3
- Performance on Yelp 2015 (HAN)
- ValueError: Dimensions must be equal, but are 15 and 100 for '{{node Equal}} = Equal[T=DT_BOOL, incompatible_shape_error=true](mask, SequenceMask/Less)' with input shapes: [?,15,100], [?,100,?]. HOT 1
- Getting error on TimeDistributed()
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from textclassifier.