(t, name)
| 63 | tensor = preprocess_offset(placeholder) if preprocess_offset else placeholder |
| 64 | |
| 65 | def offset_data(t, name): |
| 66 | input_len = shape[0] |
| 67 | if not hasattr(placeholder, 'zero_offset'): |
| 68 | placeholder.zero_offset = tf.placeholder_with_default( |
| 69 | input_len - 1, # If no zero_offset is given assume that t = 0 |
| 70 | (), |
| 71 | name + '/zero_offset') |
| 72 | |
| 73 | end = t + 1 |
| 74 | start = end - input_len |
| 75 | zero_offset = placeholder.zero_offset |
| 76 | offset_tensor = tensor[:, start + zero_offset:end + zero_offset] |
| 77 | |
| 78 | input_range = np.arange(start, end) |
| 79 | offset_tensor.required_feeds = RequiredFeeds(placeholder, input_range) |
| 80 | |
| 81 | return tf.reshape(offset_tensor, [-1] + shape, name) |
| 82 | |
| 83 | placeholder.offset_data = offset_data |
| 84 | return placeholder |
nothing calls this directly
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