tf.contrib.lookup.MutableHashTable
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A generic mutable hash table implementation.
Inherits From: LookupInterface
tf.contrib.lookup.MutableHashTable(
key_dtype, value_dtype, default_value, name='MutableHashTable', checkpoint=True
)
Data can be inserted by calling the insert method and removed by calling the
remove method. It does not support initialization via the init method.
Example usage:
table = tf.lookup.MutableHashTable(key_dtype=tf.string, value_dtype=tf.int64,
default_value=-1)
sess.run(table.insert(keys, values))
out = table.lookup(query_keys)
print(out.eval())
Args |
|---|
key_dtype
|
the type of the key tensors.
|
value_dtype
|
the type of the value tensors.
|
default_value
|
The value to use if a key is missing in the table.
|
name
|
A name for the operation (optional).
|
checkpoint
|
if True, the contents of the table are saved to and restored
from checkpoints. If shared_name is empty for a checkpointed table, it
is shared using the table node name.
|
Raises |
|---|
ValueError
|
If checkpoint is True and no name was specified.
|
Attributes |
|---|
key_dtype
|
The table key dtype.
|
name
|
The name of the table.
|
resource_handle
|
Returns the resource handle associated with this Resource.
|
value_dtype
|
The table value dtype.
|
Methods
export
View source
export(
name=None
)
Returns tensors of all keys and values in the table.
| Args |
|---|
name
|
A name for the operation (optional).
|
| Returns |
|---|
|
A pair of tensors with the first tensor containing all keys and the
second tensors containing all values in the table.
|
insert
View source
insert(
keys, values, name=None
)
Associates keys with values.
| Args |
|---|
keys
|
Keys to insert. Can be a tensor of any shape. Must match the table's
key type.
|
values
|
Values to be associated with keys. Must be a tensor of the same
shape as keys and match the table's value type.
|
name
|
A name for the operation (optional).
|
| Returns |
|---|
|
The created Operation.
|
| Raises |
|---|
TypeError
|
when keys or values doesn't match the table data
types.
|
lookup
View source
lookup(
keys, name=None
)
Looks up keys in a table, outputs the corresponding values.
The default_value is used for keys not present in the table.
| Args |
|---|
keys
|
Keys to look up. Can be a tensor of any shape. Must match the
table's key_dtype.
|
name
|
A name for the operation (optional).
|
| Returns |
|---|
A tensor containing the values in the same shape as keys using the
table's value type.
|
| Raises |
|---|
TypeError
|
when keys do not match the table data types.
|
remove
View source
remove(
keys, name=None
)
Removes keys and its associated values from the table.
If a key is not present in the table, it is silently ignored.
| Args |
|---|
keys
|
Keys to remove. Can be a tensor of any shape. Must match the table's
key type.
|
name
|
A name for the operation (optional).
|
| Returns |
|---|
|
The created Operation.
|
| Raises |
|---|
TypeError
|
when keys do not match the table data types.
|
size
View source
size(
name=None
)
Compute the number of elements in this table.
| Args |
|---|
name
|
A name for the operation (optional).
|
| Returns |
|---|
|
A scalar tensor containing the number of elements in this table.
|
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Last updated 2020-10-01 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2020-10-01 UTC."],[],[],null,["# tf.contrib.lookup.MutableHashTable\n\n\u003cbr /\u003e\n\n|--------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/ops/lookup_ops.py#L1594-L1827) |\n\nA generic mutable hash table implementation.\n\nInherits From: [`LookupInterface`](../../../tf/contrib/lookup/LookupInterface) \n\n tf.contrib.lookup.MutableHashTable(\n key_dtype, value_dtype, default_value, name='MutableHashTable', checkpoint=True\n )\n\nData can be inserted by calling the insert method and removed by calling the\nremove method. It does not support initialization via the init method.\n\n#### Example usage:\n\n table = tf.lookup.MutableHashTable(key_dtype=tf.string, value_dtype=tf.int64,\n default_value=-1)\n sess.run(table.insert(keys, values))\n out = table.lookup(query_keys)\n print(out.eval())\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|-----------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `key_dtype` | the type of the key tensors. |\n| `value_dtype` | the type of the value tensors. |\n| `default_value` | The value to use if a key is missing in the table. |\n| `name` | A name for the operation (optional). |\n| `checkpoint` | if True, the contents of the table are saved to and restored from checkpoints. If `shared_name` is empty for a checkpointed table, it is shared using the table node name. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ------ ||\n|--------------|--------------------------------------------------|\n| `ValueError` | If checkpoint is True and no name was specified. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Attributes ---------- ||\n|-------------------|------------------------------------------------------------|\n| `key_dtype` | The table key dtype. |\n| `name` | The name of the table. |\n| `resource_handle` | Returns the resource handle associated with this Resource. |\n| `value_dtype` | The table value dtype. |\n\n\u003cbr /\u003e\n\nMethods\n-------\n\n### `export`\n\n[View source](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/ops/lookup_ops.py#L1783-L1798) \n\n export(\n name=None\n )\n\nReturns tensors of all keys and values in the table.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|--------|--------------------------------------|\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| A pair of tensors with the first tensor containing all keys and the second tensors containing all values in the table. ||\n\n\u003cbr /\u003e\n\n### `insert`\n\n[View source](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/ops/lookup_ops.py#L1756-L1781) \n\n insert(\n keys, values, name=None\n )\n\nAssociates `keys` with `values`.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|----------|-------------------------------------------------------------------------------------------------------------------|\n| `keys` | Keys to insert. Can be a tensor of any shape. Must match the table's key type. |\n| `values` | Values to be associated with keys. Must be a tensor of the same shape as `keys` and match the table's value type. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| The created Operation. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ||\n|-------------|-------------------------------------------------------------|\n| `TypeError` | when `keys` or `values` doesn't match the table data types. |\n\n\u003cbr /\u003e\n\n### `lookup`\n\n[View source](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/ops/lookup_ops.py#L1731-L1754) \n\n lookup(\n keys, name=None\n )\n\nLooks up `keys` in a table, outputs the corresponding values.\n\nThe `default_value` is used for keys not present in the table.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|--------|----------------------------------------------------------------------------------|\n| `keys` | Keys to look up. Can be a tensor of any shape. Must match the table's key_dtype. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| A tensor containing the values in the same shape as `keys` using the table's value type. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ||\n|-------------|------------------------------------------------|\n| `TypeError` | when `keys` do not match the table data types. |\n\n\u003cbr /\u003e\n\n### `remove`\n\n[View source](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/ops/lookup_ops.py#L1705-L1729) \n\n remove(\n keys, name=None\n )\n\nRemoves `keys` and its associated values from the table.\n\nIf a key is not present in the table, it is silently ignored.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|--------|--------------------------------------------------------------------------------|\n| `keys` | Keys to remove. Can be a tensor of any shape. Must match the table's key type. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| The created Operation. ||\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Raises ||\n|-------------|------------------------------------------------|\n| `TypeError` | when `keys` do not match the table data types. |\n\n\u003cbr /\u003e\n\n### `size`\n\n[View source](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/ops/lookup_ops.py#L1692-L1703) \n\n size(\n name=None\n )\n\nCompute the number of elements in this table.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ||\n|--------|--------------------------------------|\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ||\n|---|---|\n| A scalar tensor containing the number of elements in this table. ||\n\n\u003cbr /\u003e"]]
View source on GitHub