Constructs a graph mode TensorArray. Args: dtype: (required) data type of the TensorArray. size: (optional) int32 scalar `Tensor`: the size of the TensorArray. Required if handle is not provided. dynamic_size: (optional) Python bool: If true, writes to the TensorArray
(self,
dtype,
size=None,
dynamic_size=None,
clear_after_read=None,
tensor_array_name=None,
handle=None,
flow=None,
infer_shape=True,
element_shape=None,
colocate_with_first_write_call=True,
name=None)
| 51 | """ |
| 52 | |
| 53 | def __init__(self, |
| 54 | dtype, |
| 55 | size=None, |
| 56 | dynamic_size=None, |
| 57 | clear_after_read=None, |
| 58 | tensor_array_name=None, |
| 59 | handle=None, |
| 60 | flow=None, |
| 61 | infer_shape=True, |
| 62 | element_shape=None, |
| 63 | colocate_with_first_write_call=True, |
| 64 | name=None): |
| 65 | """Constructs a graph mode TensorArray. |
| 66 | |
| 67 | Args: |
| 68 | dtype: (required) data type of the TensorArray. |
| 69 | size: (optional) int32 scalar `Tensor`: the size of the TensorArray. |
| 70 | Required if handle is not provided. |
| 71 | dynamic_size: (optional) Python bool: If true, writes to the TensorArray |
| 72 | can grow the TensorArray past its initial size. Default: False. |
| 73 | clear_after_read: Boolean (optional, default: True). If True, clear |
| 74 | TensorArray values after reading them. This disables read-many |
| 75 | semantics, but allows early release of memory. |
| 76 | tensor_array_name: (optional) Python string: the name of the TensorArray. |
| 77 | This is used when creating the TensorArray handle. If this value is |
| 78 | set, handle should be None. |
| 79 | handle: (optional) A `Tensor` handle to an existing TensorArray. If this |
| 80 | is set, tensor_array_name should be None. Only supported in graph mode. |
| 81 | flow: (optional) A float `Tensor` scalar coming from an existing |
| 82 | `TensorArray.flow`. Only supported in graph mode. |
| 83 | infer_shape: (optional, default: True) If True, shape inference |
| 84 | is enabled. In this case, all elements must have the same shape. |
| 85 | element_shape: (optional, default: None) A `TensorShape` object specifying |
| 86 | the shape constraints of each of the elements of the TensorArray. |
| 87 | Need not be fully defined. |
| 88 | colocate_with_first_write_call: If `True`, the TensorArray will be |
| 89 | colocated on the same device as the Tensor used on its first write |
| 90 | (write operations include `write`, `unstack`, and `split`). If `False`, |
| 91 | the TensorArray will be placed on the device determined by the |
| 92 | device context available during its initialization. |
| 93 | name: A name for the operation (optional). |
| 94 | |
| 95 | Raises: |
| 96 | ValueError: if both handle and tensor_array_name are provided. |
| 97 | TypeError: if handle is provided but is not a Tensor. |
| 98 | """ |
| 99 | if handle is not None and tensor_array_name: |
| 100 | raise ValueError( |
| 101 | "Cannot construct with both handle and tensor_array_name") |
| 102 | if handle is not None and not isinstance(handle, ops.Tensor): |
| 103 | raise TypeError("Handle must be a Tensor") |
| 104 | if handle is None and size is None: |
| 105 | raise ValueError("Size must be provided if handle is not provided") |
| 106 | if handle is not None and size is not None: |
| 107 | raise ValueError("Cannot provide both a handle and size " |
| 108 | "at the same time") |
| 109 | if handle is not None and element_shape is not None: |
| 110 | raise ValueError("Cannot provide both a handle and element_shape " |
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