Nrthugu

i have two Tensors, like this:

>>> xx_idx

<tf.Tensor 'Placeholder:0' shape=(100, ?) dtype=int64>

>>> xx_val

<tf.Tensor 'Placeholder_1:0' shape=(100, ?) dtype=float64>

How to create a SparseTensor from them? xx_idx are the indexes, xx_val are the values.
There are 100 samples.
The dimension of the vector is unknown, maybe 22000.

I tried this:

xx_vec = tf.SparseTensor(xx_idx, xx_val, 25000)

but here comes the error:

Traceback (most recent call last):

  File "<stdin>", line 1, in <module>

NameError: name 'user_idx' is not defined

>>> xx_vec = tf.SparseTensor(xx_idx, xx_val, 25000)

Traceback (most recent call last):

  File "/home/work/tf/lib/python3.5/site-packages/tensorflow/python/framework/tensor_shape.py", line 671, in merge_with

    self.assert_same_rank(other)

  File "/home/work/tf/lib/python3.5/site-packages/tensorflow/python/framework/tensor_shape.py", line 716, in assert_same_rank

    other))

ValueError: Shapes (100, ?) and (?,) must have the same rank



During handling of the above exception, another exception occurred:



Traceback (most recent call last):

  File "/home/work/tf/lib/python3.5/site-packages/tensorflow/python/framework/tensor_shape.py", line 746, in with_rank

    return self.merge_with(unknown_shape(ndims=rank))

  File "/home/work/tf/lib/python3.5/site-packages/tensorflow/python/framework/tensor_shape.py", line 677, in merge_with

    raise ValueError("Shapes %s and %s are not compatible" % (self, other))

ValueError: Shapes (100, ?) and (?,) are not compatible



During handling of the above exception, another exception occurred:



Traceback (most recent call last):

  File "<stdin>", line 1, in <module>

  File "/home/work/tf/lib/python3.5/site-packages/tensorflow/python/framework/sparse_tensor.py", line 133, in __init__

    values_shape = values.get_shape().with_rank(1)

  File "/home/work/tf/lib/python3.5/site-packages/tensorflow/python/framework/tensor_shape.py", line 748, in with_rank

    raise ValueError("Shape %s must have rank %d" % (self, rank))

ValueError: Shape (100, ?) must have rank 1

problem solved

import tensorflow as tf

from tensorflow import TensorShape, Dimension





class GetVector:



    @classmethod

    def get_sparse_vector(cls, idx_all_0, val_all, dim_num):

        batch_size = idx_all_0.shape[0].value

        '''

        cur_idx = tf.placeholder(tf.int64, [batch_size, None, 1])

        cur_val = tf.placeholder(tf.float64, [batch_size, None])

        cur_vec = tf.placeholder(tf.float64, [batch_size, dim_num])

        '''

        idx_all = cls.idx_reform(idx_all_0)



        ans = 

        for i in range(batch_size):

            cur_idx = idx_all[i]

            cur_val = val_all[i]

            cur_vec = tf.SparseTensor(cur_idx, cur_val, TensorShape(Dimension(dim_num)))

            cur_vec_tensor = tf.sparse_tensor_to_dense(cur_vec)

            ans = tf.concat([ans, cur_vec_tensor], 0)

        ans = tf.reshape(ans, [batch_size, dim_num])

        return ans



    @classmethod

    def idx_reform(cls, idx_all):

        batch_size = idx_all.shape[0].value

        return tf.reshape(idx_all, [batch_size, -1, 1])