impl_helper_test.py 文件源码

python
阅读 24 收藏 0 点赞 0 评论 0

项目:transform 作者: tensorflow 项目源码 文件源码
def testRunPreprocessingFn(self):
    schema = self.toSchema({
        'dense_1': tf.FixedLenFeature((), tf.float32),
        'dense_2': tf.FixedLenFeature((1, 2), tf.int64),
        'var_len': tf.VarLenFeature(tf.string),
        'sparse': tf.SparseFeature('ix', 'val', tf.float32, 100)
    })
    def preprocessing_fn(inputs):
      return {
          'dense_out': mappers.scale_to_0_1(inputs['dense_1']),
          'sparse_out': tf.sparse_reshape(inputs['sparse'], (1, 10)),
      }

    _, inputs, outputs = impl_helper.run_preprocessing_fn(
        preprocessing_fn, schema)

    # Verify that the input placeholders have the correct types.
    expected_dtype_and_shape = {
        'dense_1': (tf.float32, tf.TensorShape([None])),
        'dense_2': (tf.int64, tf.TensorShape([None, 1, 2])),
        'var_len': (tf.string, tf.TensorShape([None, None])),
        'sparse': (tf.float32, tf.TensorShape([None, None])),
        'dense_out': (tf.float32, tf.TensorShape([None])),
        'sparse_out': (tf.float32, tf.TensorShape([None, None])),
    }

    for key, tensor in itertools.chain(six.iteritems(inputs),
                                       six.iteritems(outputs)):
      dtype, shape = expected_dtype_and_shape[key]
      self.assertEqual(tensor.dtype, dtype)
      tensor.get_shape().assert_is_compatible_with(shape)
评论列表
文章目录


问题


面经


文章

微信
公众号

扫码关注公众号