Update generated Python Op docs.
Change: 143129041
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### `tf_debug.watch_graph_with_blacklists(run_options, graph, debug_ops='DebugIdentity', debug_urls=None, node_name_regex_blacklist=None, op_type_regex_blacklist=None)` {#watch_graph_with_blacklists}
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Add debug tensor watches, blacklisting nodes and op types.
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This is similar to `watch_graph()`, but the node names and op types are
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blacklisted, instead of whitelisted.
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N.B.: Under certain circumstances, not all specified `Tensor`s will be
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actually watched (e.g., nodes that are constant-folded during runtime will
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not be watched).
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##### Args:
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* <b>`run_options`</b>: An instance of `config_pb2.RunOptions` to be modified.
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* <b>`graph`</b>: An instance of `ops.Graph`.
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* <b>`debug_ops`</b>: (`str` or `list` of `str`) name(s) of the debug op(s) to use.
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* <b>`debug_urls`</b>: URL(s) to send ebug values to, e.g.,
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`file:///tmp/tfdbg_dump_1`, `grpc://localhost:12345`.
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* <b>`node_name_regex_blacklist`</b>: Regular-expression blacklist for node_name.
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This should be a string, e.g., `"(weight_[0-9]+|bias_.*)"`.
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* <b>`op_type_regex_blacklist`</b>: Regular-expression blacklist for the op type of
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nodes, e.g., `"(Variable|Add)"`.
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If both node_name_regex_blacklist and op_type_regex_blacklist
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are set, the two filtering operations will occur in a logical `OR`
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relation. In other words, a node will be excluded if it hits either of
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the two blacklists; a node will be included if and only if it hits
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neither of the blacklists.
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Command-line-interface debugger hook.
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Can be used as a monitor/hook for tf.train.MonitoredSession.
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- - -
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#### `tf_debug.LocalCLIDebugHook.__enter__()` {#LocalCLIDebugHook.__enter__}
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- - -
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#### `tf_debug.LocalCLIDebugHook.__exit__(exec_type, exec_value, exec_tb)` {#LocalCLIDebugHook.__exit__}
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- - -
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#### `tf_debug.LocalCLIDebugHook.__init__()` {#LocalCLIDebugHook.__init__}
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Create a local debugger command-line interface (CLI) hook.
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- - -
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#### `tf_debug.LocalCLIDebugHook.add_tensor_filter(filter_name, tensor_filter)` {#LocalCLIDebugHook.add_tensor_filter}
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Add a tensor filter.
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##### Args:
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* <b>`filter_name`</b>: (`str`) name of the filter.
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* <b>`tensor_filter`</b>: (`callable`) the filter callable. See the doc string of
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`DebugDumpDir.find()` for more details about its signature.
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- - -
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#### `tf_debug.LocalCLIDebugHook.after_create_session(session)` {#LocalCLIDebugHook.after_create_session}
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Called when new TensorFlow session is created.
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This is called to signal the hooks that a new session has been created. This
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has two essential differences with the situation in which `begin` is called:
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* When this is called, the graph is finalized and ops can no longer be added
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to the graph.
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* This method will also be called as a result of recovering a wrapped
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session, not only at the beginning of the overall session.
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##### Args:
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* <b>`session`</b>: A TensorFlow Session that has been created.
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- - -
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#### `tf_debug.LocalCLIDebugHook.after_run(run_context, run_values)` {#LocalCLIDebugHook.after_run}
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- - -
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#### `tf_debug.LocalCLIDebugHook.before_run(run_context)` {#LocalCLIDebugHook.before_run}
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- - -
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#### `tf_debug.LocalCLIDebugHook.begin()` {#LocalCLIDebugHook.begin}
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- - -
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#### `tf_debug.LocalCLIDebugHook.close()` {#LocalCLIDebugHook.close}
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- - -
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#### `tf_debug.LocalCLIDebugHook.end(session)` {#LocalCLIDebugHook.end}
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Called at the end of session.
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The `session` argument can be used in case the hook wants to run final ops,
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such as saving a last checkpoint.
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##### Args:
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* <b>`session`</b>: A TensorFlow Session that will be soon closed.
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- - -
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#### `tf_debug.LocalCLIDebugHook.graph` {#LocalCLIDebugHook.graph}
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- - -
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#### `tf_debug.LocalCLIDebugHook.invoke_node_stepper(node_stepper, restore_variable_values_on_exit=True)` {#LocalCLIDebugHook.invoke_node_stepper}
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Overrides method in base class to implement interactive node stepper.
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##### Args:
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* <b>`node_stepper`</b>: (`stepper.NodeStepper`) The underlying NodeStepper API
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object.
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* <b>`restore_variable_values_on_exit`</b>: (`bool`) Whether any variables whose
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values have been altered during this node-stepper invocation should be
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restored to their old values when this invocation ends.
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##### Returns:
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The same return values as the `Session.run()` call on the same fetches as
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the NodeStepper.
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- - -
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#### `tf_debug.LocalCLIDebugHook.on_run_end(request)` {#LocalCLIDebugHook.on_run_end}
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Overrides on-run-end callback.
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##### Actions taken:
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1) Load the debug dump.
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2) Bring up the Analyzer CLI.
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##### Args:
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* <b>`request`</b>: An instance of OnSessionInitRequest.
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##### Returns:
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An instance of OnSessionInitResponse.
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- - -
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#### `tf_debug.LocalCLIDebugHook.on_run_start(request)` {#LocalCLIDebugHook.on_run_start}
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Overrides on-run-start callback.
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##### Invoke the CLI to let user choose what action to take:
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`run` / `invoke_stepper`.
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##### Args:
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* <b>`request`</b>: An instance of `OnSessionInitRequest`.
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##### Returns:
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An instance of `OnSessionInitResponse`.
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##### Raises:
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* <b>`RuntimeError`</b>: If user chooses to prematurely exit the debugger.
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- - -
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#### `tf_debug.LocalCLIDebugHook.on_session_init(request)` {#LocalCLIDebugHook.on_session_init}
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Overrides on-session-init callback.
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##### Args:
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* <b>`request`</b>: An instance of `OnSessionInitRequest`.
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##### Returns:
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An instance of OnSessionInitResponse.
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- - -
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#### `tf_debug.LocalCLIDebugHook.partial_run(handle, fetches, feed_dict=None)` {#LocalCLIDebugHook.partial_run}
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- - -
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#### `tf_debug.LocalCLIDebugHook.partial_run_setup(fetches, feeds=None)` {#LocalCLIDebugHook.partial_run_setup}
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Sets up the feeds and fetches for partial runs in the session.
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- - -
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#### `tf_debug.LocalCLIDebugHook.run(fetches, feed_dict=None, options=None, run_metadata=None)` {#LocalCLIDebugHook.run}
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Wrapper around Session.run() that inserts tensor watch options.
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##### Args:
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* <b>`fetches`</b>: Same as the `fetches` arg to regular `Session.run()`.
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* <b>`feed_dict`</b>: Same as the `feed_dict` arg to regular `Session.run()`.
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* <b>`options`</b>: Same as the `options` arg to regular `Session.run()`.
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* <b>`run_metadata`</b>: Same as the `run_metadata` arg to regular `Session.run()`.
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##### Returns:
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Simply forwards the output of the wrapped `Session.run()` call.
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##### Raises:
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* <b>`ValueError`</b>: On invalid `OnRunStartAction` value.
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- - -
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#### `tf_debug.LocalCLIDebugHook.sess_str` {#LocalCLIDebugHook.sess_str}
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- - -
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#### `tf_debug.LocalCLIDebugHook.session` {#LocalCLIDebugHook.session}
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A single tensor dumped by TensorFlow Debugger (tfdbg).
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Contains metadata about the dumped tensor, including `timestamp`,
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`node_name`, `output_slot`, `debug_op`, and path to the dump file
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(`file_path`).
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This type does not hold the generally space-expensive tensor value (numpy
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array). Instead, it points to the file from which the tensor value can be
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loaded (with the `get_tensor` method) if needed.
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- - -
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#### `tf_debug.DebugTensorDatum.__init__(dump_root, debug_dump_rel_path)` {#DebugTensorDatum.__init__}
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`DebugTensorDatum` constructor.
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##### Args:
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* <b>`dump_root`</b>: (`str`) Debug dump root directory.
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* <b>`debug_dump_rel_path`</b>: (`str`) Path to a debug dump file, relative to the
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`dump_root`. For example, suppose the debug dump root
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directory is `/tmp/tfdbg_1` and the dump file is at
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`/tmp/tfdbg_1/ns_1/node_a_0_DebugIdentity_123456789`, then
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the value of the debug_dump_rel_path should be
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`ns_1/node_a_0_DebugIdenity_1234456789`.
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##### Raises:
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* <b>`ValueError`</b>: If the base file name of the dump file does not conform to
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the dump file naming pattern:
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`node_name`_`output_slot`_`debug_op`_`timestamp`
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- - -
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#### `tf_debug.DebugTensorDatum.__repr__()` {#DebugTensorDatum.__repr__}
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- - -
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#### `tf_debug.DebugTensorDatum.__str__()` {#DebugTensorDatum.__str__}
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- - -
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#### `tf_debug.DebugTensorDatum.debug_op` {#DebugTensorDatum.debug_op}
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Name of the debug op.
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##### Returns:
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(`str`) debug op name (e.g., `DebugIdentity`).
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- - -
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#### `tf_debug.DebugTensorDatum.file_path` {#DebugTensorDatum.file_path}
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Path to the file which stores the value of the dumped tensor.
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- - -
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#### `tf_debug.DebugTensorDatum.get_tensor()` {#DebugTensorDatum.get_tensor}
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Get tensor from the dump (`Event`) file.
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##### Returns:
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The tensor loaded from the dump (`Event`) file.
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- - -
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#### `tf_debug.DebugTensorDatum.node_name` {#DebugTensorDatum.node_name}
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Name of the node from which the tensor value was dumped.
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##### Returns:
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(`str`) name of the node watched by the debug op.
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- - -
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#### `tf_debug.DebugTensorDatum.output_slot` {#DebugTensorDatum.output_slot}
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Output slot index from which the tensor value was dumped.
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##### Returns:
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(`int`) output slot index watched by the debug op.
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- - -
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#### `tf_debug.DebugTensorDatum.tensor_name` {#DebugTensorDatum.tensor_name}
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Name of the tensor watched by the debug op.
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##### Returns:
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(`str`) `Tensor` name, in the form of `node_name`:`output_slot`
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- - -
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#### `tf_debug.DebugTensorDatum.timestamp` {#DebugTensorDatum.timestamp}
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Timestamp of when this tensor value was dumped.
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##### Returns:
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(`int`) The timestamp in microseconds.
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- - -
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#### `tf_debug.DebugTensorDatum.watch_key` {#DebugTensorDatum.watch_key}
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Watch key identities a debug watch on a tensor.
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##### Returns:
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(`str`) A watch key, in the form of `tensor_name`:`debug_op`.
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Concrete subclass of BaseDebugWrapperSession implementing a local CLI.
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This class has all the methods that a `session.Session` object has, in order
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to support debugging with minimal code changes. Invoking its `run()` method
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will launch the command-line interface (CLI) of tfdbg.
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- - -
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#### `tf_debug.LocalCLIDebugWrapperSession.__enter__()` {#LocalCLIDebugWrapperSession.__enter__}
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- - -
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#### `tf_debug.LocalCLIDebugWrapperSession.__exit__(exec_type, exec_value, exec_tb)` {#LocalCLIDebugWrapperSession.__exit__}
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- - -
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#### `tf_debug.LocalCLIDebugWrapperSession.__init__(sess, dump_root=None, log_usage=True)` {#LocalCLIDebugWrapperSession.__init__}
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Constructor of LocalCLIDebugWrapperSession.
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##### Args:
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* <b>`sess`</b>: The TensorFlow `Session` object being wrapped.
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* <b>`dump_root`</b>: (`str`) optional path to the dump root directory. Must be a
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directory that does not exist or an empty directory. If the directory
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does not exist, it will be created by the debugger core during debug
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`run()` calls and removed afterwards.
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* <b>`log_usage`</b>: (`bool`) whether the usage of this class is to be logged.
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##### Raises:
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* <b>`ValueError`</b>: If dump_root is an existing and non-empty directory or if
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dump_root is a file.
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- - -
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#### `tf_debug.LocalCLIDebugWrapperSession.add_tensor_filter(filter_name, tensor_filter)` {#LocalCLIDebugWrapperSession.add_tensor_filter}
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Add a tensor filter.
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##### Args:
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* <b>`filter_name`</b>: (`str`) name of the filter.
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* <b>`tensor_filter`</b>: (`callable`) the filter callable. See the doc string of
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`DebugDumpDir.find()` for more details about its signature.
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- - -
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#### `tf_debug.LocalCLIDebugWrapperSession.close()` {#LocalCLIDebugWrapperSession.close}
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- - -
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#### `tf_debug.LocalCLIDebugWrapperSession.graph` {#LocalCLIDebugWrapperSession.graph}
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- - -
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#### `tf_debug.LocalCLIDebugWrapperSession.invoke_node_stepper(node_stepper, restore_variable_values_on_exit=True)` {#LocalCLIDebugWrapperSession.invoke_node_stepper}
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Overrides method in base class to implement interactive node stepper.
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##### Args:
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* <b>`node_stepper`</b>: (`stepper.NodeStepper`) The underlying NodeStepper API
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object.
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* <b>`restore_variable_values_on_exit`</b>: (`bool`) Whether any variables whose
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values have been altered during this node-stepper invocation should be
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restored to their old values when this invocation ends.
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##### Returns:
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The same return values as the `Session.run()` call on the same fetches as
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the NodeStepper.
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- - -
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#### `tf_debug.LocalCLIDebugWrapperSession.on_run_end(request)` {#LocalCLIDebugWrapperSession.on_run_end}
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Overrides on-run-end callback.
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##### Actions taken:
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1) Load the debug dump.
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2) Bring up the Analyzer CLI.
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##### Args:
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* <b>`request`</b>: An instance of OnSessionInitRequest.
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##### Returns:
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An instance of OnSessionInitResponse.
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- - -
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#### `tf_debug.LocalCLIDebugWrapperSession.on_run_start(request)` {#LocalCLIDebugWrapperSession.on_run_start}
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Overrides on-run-start callback.
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##### Invoke the CLI to let user choose what action to take:
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`run` / `invoke_stepper`.
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##### Args:
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* <b>`request`</b>: An instance of `OnSessionInitRequest`.
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##### Returns:
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||||
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||||
An instance of `OnSessionInitResponse`.
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||||
##### Raises:
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||||
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||||
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* <b>`RuntimeError`</b>: If user chooses to prematurely exit the debugger.
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||||
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- - -
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#### `tf_debug.LocalCLIDebugWrapperSession.on_session_init(request)` {#LocalCLIDebugWrapperSession.on_session_init}
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|
||||
Overrides on-session-init callback.
|
||||
|
||||
##### Args:
|
||||
|
||||
|
||||
* <b>`request`</b>: An instance of `OnSessionInitRequest`.
|
||||
|
||||
##### Returns:
|
||||
|
||||
An instance of OnSessionInitResponse.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.LocalCLIDebugWrapperSession.partial_run(handle, fetches, feed_dict=None)` {#LocalCLIDebugWrapperSession.partial_run}
|
||||
|
||||
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.LocalCLIDebugWrapperSession.partial_run_setup(fetches, feeds=None)` {#LocalCLIDebugWrapperSession.partial_run_setup}
|
||||
|
||||
Sets up the feeds and fetches for partial runs in the session.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.LocalCLIDebugWrapperSession.run(fetches, feed_dict=None, options=None, run_metadata=None)` {#LocalCLIDebugWrapperSession.run}
|
||||
|
||||
Wrapper around Session.run() that inserts tensor watch options.
|
||||
|
||||
##### Args:
|
||||
|
||||
|
||||
* <b>`fetches`</b>: Same as the `fetches` arg to regular `Session.run()`.
|
||||
* <b>`feed_dict`</b>: Same as the `feed_dict` arg to regular `Session.run()`.
|
||||
* <b>`options`</b>: Same as the `options` arg to regular `Session.run()`.
|
||||
* <b>`run_metadata`</b>: Same as the `run_metadata` arg to regular `Session.run()`.
|
||||
|
||||
##### Returns:
|
||||
|
||||
Simply forwards the output of the wrapped `Session.run()` call.
|
||||
|
||||
##### Raises:
|
||||
|
||||
|
||||
* <b>`ValueError`</b>: On invalid `OnRunStartAction` value.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.LocalCLIDebugWrapperSession.sess_str` {#LocalCLIDebugWrapperSession.sess_str}
|
||||
|
||||
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.LocalCLIDebugWrapperSession.session` {#LocalCLIDebugWrapperSession.session}
|
||||
|
||||
|
||||
|
||||
|
@ -0,0 +1,19 @@
|
||||
### `tf_debug.add_debug_tensor_watch(run_options, node_name, output_slot=0, debug_ops='DebugIdentity', debug_urls=None)` {#add_debug_tensor_watch}
|
||||
|
||||
Add watch on a `Tensor` to `RunOptions`.
|
||||
|
||||
N.B.: Under certain circumstances, the `Tensor` may not be actually watched
|
||||
(e.g., if the node of the `Tensor` is constant-folded during runtime).
|
||||
|
||||
##### Args:
|
||||
|
||||
|
||||
* <b>`run_options`</b>: An instance of `config_pb2.RunOptions` to be modified.
|
||||
* <b>`node_name`</b>: (`str`) name of the node to watch.
|
||||
* <b>`output_slot`</b>: (`int`) output slot index of the tensor from the watched node.
|
||||
* <b>`debug_ops`</b>: (`str` or `list` of `str`) name(s) of the debug op(s). Can be a
|
||||
`list` of `str` or a single `str`. The latter case is equivalent to a
|
||||
`list` of `str` with only one element.
|
||||
* <b>`debug_urls`</b>: (`str` or `list` of `str`) URL(s) to send debug values to,
|
||||
e.g., `file:///tmp/tfdbg_dump_1`, `grpc://localhost:12345`.
|
||||
|
@ -0,0 +1,17 @@
|
||||
### `tf_debug.load_tensor_from_event_file(event_file_path)` {#load_tensor_from_event_file}
|
||||
|
||||
Load a tensor from an event file.
|
||||
|
||||
Assumes that the event file contains a `Event` protobuf and the `Event`
|
||||
protobuf contains a `Tensor` value.
|
||||
|
||||
##### Args:
|
||||
|
||||
|
||||
* <b>`event_file_path`</b>: (`str`) path to the event file.
|
||||
|
||||
##### Returns:
|
||||
|
||||
The tensor value loaded from the event file, as a `numpy.ndarray`. For
|
||||
uninitialized tensors, returns None.
|
||||
|
@ -0,0 +1,467 @@
|
||||
Data set from a debug-dump directory on filesystem.
|
||||
|
||||
An instance of `DebugDumpDir` contains all `DebugTensorDatum` instances
|
||||
in a tfdbg dump root directory.
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.__init__(dump_root, partition_graphs=None, validate=True)` {#DebugDumpDir.__init__}
|
||||
|
||||
`DebugDumpDir` constructor.
|
||||
|
||||
##### Args:
|
||||
|
||||
|
||||
* <b>`dump_root`</b>: (`str`) path to the dump root directory.
|
||||
* <b>`partition_graphs`</b>: A repeated field of GraphDefs representing the
|
||||
partition graphs executed by the TensorFlow runtime.
|
||||
* <b>`validate`</b>: (`bool`) whether the dump files are to be validated against the
|
||||
partition graphs.
|
||||
|
||||
##### Raises:
|
||||
|
||||
|
||||
* <b>`IOError`</b>: If dump_root does not exist as a directory.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.debug_watch_keys(node_name)` {#DebugDumpDir.debug_watch_keys}
|
||||
|
||||
Get all tensor watch keys of given node according to partition graphs.
|
||||
|
||||
##### Args:
|
||||
|
||||
|
||||
* <b>`node_name`</b>: (`str`) name of the node.
|
||||
|
||||
##### Returns:
|
||||
|
||||
(`list` of `str`) all debug tensor watch keys. Returns an empty list if
|
||||
the node name does not correspond to any debug watch keys.
|
||||
|
||||
##### Raises:
|
||||
|
||||
`LookupError`: If debug watch information has not been loaded from
|
||||
partition graphs yet.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.devices()` {#DebugDumpDir.devices}
|
||||
|
||||
Get the list of devices.
|
||||
|
||||
##### Returns:
|
||||
|
||||
(`list` of `str`) names of the devices.
|
||||
|
||||
##### Raises:
|
||||
|
||||
|
||||
* <b>`LookupError`</b>: If node inputs and control inputs have not been loaded
|
||||
from partition graphs yet.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.dumped_tensor_data` {#DebugDumpDir.dumped_tensor_data}
|
||||
|
||||
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.find(predicate, first_n=0)` {#DebugDumpDir.find}
|
||||
|
||||
Find dumped tensor data by a certain predicate.
|
||||
|
||||
##### Args:
|
||||
|
||||
|
||||
* <b>`predicate`</b>: A callable that takes two input arguments:
|
||||
|
||||
```python
|
||||
def predicate(debug_tensor_datum, tensor):
|
||||
# returns a bool
|
||||
```
|
||||
|
||||
where `debug_tensor_datum` is an instance of `DebugTensorDatum`, which
|
||||
carries the metadata, such as the `Tensor`'s node name, output slot
|
||||
timestamp, debug op name, etc.; and `tensor` is the dumped tensor value
|
||||
as a `numpy.ndarray`.
|
||||
|
||||
* <b>`first_n`</b>: (`int`) return only the first n `DebugTensotDatum` instances (in
|
||||
time order) for which the predicate returns True. To return all the
|
||||
`DebugTensotDatum` instances, let first_n be <= 0.
|
||||
|
||||
##### Returns:
|
||||
|
||||
A list of all `DebugTensorDatum` objects in this `DebugDumpDir` object
|
||||
for which predicate returns True, sorted in ascending order of the
|
||||
timestamp.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.get_rel_timestamps(node_name, output_slot, debug_op)` {#DebugDumpDir.get_rel_timestamps}
|
||||
|
||||
Get the relative timestamp from for a debug-dumped tensor.
|
||||
|
||||
Relative timestamp means (absolute timestamp - `t0`), where `t0` is the
|
||||
absolute timestamp of the first dumped tensor in the dump root. The tensor
|
||||
may be dumped multiple times in the dump root directory, so a list of
|
||||
relative timestamps (`numpy.ndarray`) is returned.
|
||||
|
||||
##### Args:
|
||||
|
||||
|
||||
* <b>`node_name`</b>: (`str`) name of the node that the tensor is produced by.
|
||||
* <b>`output_slot`</b>: (`int`) output slot index of tensor.
|
||||
* <b>`debug_op`</b>: (`str`) name of the debug op.
|
||||
|
||||
##### Returns:
|
||||
|
||||
(list of int) list of relative timestamps.
|
||||
|
||||
##### Raises:
|
||||
|
||||
|
||||
* <b>`ValueError`</b>: If the tensor does not exist in the debub dump data.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.get_tensor_file_paths(node_name, output_slot, debug_op)` {#DebugDumpDir.get_tensor_file_paths}
|
||||
|
||||
Get the file paths from a debug-dumped tensor.
|
||||
|
||||
##### Args:
|
||||
|
||||
|
||||
* <b>`node_name`</b>: (`str`) name of the node that the tensor is produced by.
|
||||
* <b>`output_slot`</b>: (`int`) output slot index of tensor.
|
||||
* <b>`debug_op`</b>: (`str`) name of the debug op.
|
||||
|
||||
##### Returns:
|
||||
|
||||
List of file path(s) loaded. This is a list because each debugged tensor
|
||||
may be dumped multiple times.
|
||||
|
||||
##### Raises:
|
||||
|
||||
|
||||
* <b>`ValueError`</b>: If the tensor does not exist in the debug-dump data.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.get_tensors(node_name, output_slot, debug_op)` {#DebugDumpDir.get_tensors}
|
||||
|
||||
Get the tensor value from for a debug-dumped tensor.
|
||||
|
||||
The tensor may be dumped multiple times in the dump root directory, so a
|
||||
list of tensors (`numpy.ndarray`) is returned.
|
||||
|
||||
##### Args:
|
||||
|
||||
|
||||
* <b>`node_name`</b>: (`str`) name of the node that the tensor is produced by.
|
||||
* <b>`output_slot`</b>: (`int`) output slot index of tensor.
|
||||
* <b>`debug_op`</b>: (`str`) name of the debug op.
|
||||
|
||||
##### Returns:
|
||||
|
||||
List of tensors (`numpy.ndarray`) loaded from the debug-dump file(s).
|
||||
|
||||
##### Raises:
|
||||
|
||||
|
||||
* <b>`ValueError`</b>: If the tensor does not exist in the debug-dump data.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.loaded_partition_graphs()` {#DebugDumpDir.loaded_partition_graphs}
|
||||
|
||||
Test whether partition graphs have been loaded.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.node_attributes(node_name)` {#DebugDumpDir.node_attributes}
|
||||
|
||||
Get the attributes of a node.
|
||||
|
||||
##### Args:
|
||||
|
||||
|
||||
* <b>`node_name`</b>: Name of the node in question.
|
||||
|
||||
##### Returns:
|
||||
|
||||
Attributes of the node.
|
||||
|
||||
##### Raises:
|
||||
|
||||
|
||||
* <b>`LookupError`</b>: If no partition graphs have been loaded.
|
||||
* <b>`ValueError`</b>: If no node named node_name exists.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.node_device(node_name)` {#DebugDumpDir.node_device}
|
||||
|
||||
Get the device of a node.
|
||||
|
||||
##### Args:
|
||||
|
||||
|
||||
* <b>`node_name`</b>: (`str`) name of the node.
|
||||
|
||||
##### Returns:
|
||||
|
||||
(`str`) name of the device on which the node is placed.
|
||||
|
||||
##### Raises:
|
||||
|
||||
|
||||
* <b>`LookupError`</b>: If node inputs and control inputs have not been loaded
|
||||
from partition graphs yet.
|
||||
* <b>`ValueError`</b>: If the node does not exist in partition graphs.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.node_exists(node_name)` {#DebugDumpDir.node_exists}
|
||||
|
||||
Test if a node exists in the partition graphs.
|
||||
|
||||
##### Args:
|
||||
|
||||
|
||||
* <b>`node_name`</b>: (`str`) name of the node to be checked.
|
||||
|
||||
##### Returns:
|
||||
|
||||
A boolean indicating whether the node exists.
|
||||
|
||||
##### Raises:
|
||||
|
||||
|
||||
* <b>`LookupError`</b>: If no partition graphs have been loaded yet.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.node_inputs(node_name, is_control=False)` {#DebugDumpDir.node_inputs}
|
||||
|
||||
Get the inputs of given node according to partition graphs.
|
||||
|
||||
##### Args:
|
||||
|
||||
|
||||
* <b>`node_name`</b>: Name of the node.
|
||||
* <b>`is_control`</b>: (`bool`) Whether control inputs, rather than non-control
|
||||
inputs, are to be returned.
|
||||
|
||||
##### Returns:
|
||||
|
||||
(`list` of `str`) inputs to the node, as a list of node names.
|
||||
|
||||
##### Raises:
|
||||
|
||||
|
||||
* <b>`LookupError`</b>: If node inputs and control inputs have not been loaded
|
||||
from partition graphs yet.
|
||||
* <b>`ValueError`</b>: If the node does not exist in partition graphs.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.node_op_type(node_name)` {#DebugDumpDir.node_op_type}
|
||||
|
||||
Get the op type of given node.
|
||||
|
||||
##### Args:
|
||||
|
||||
|
||||
* <b>`node_name`</b>: (`str`) name of the node.
|
||||
|
||||
##### Returns:
|
||||
|
||||
(`str`) op type of the node.
|
||||
|
||||
##### Raises:
|
||||
|
||||
|
||||
* <b>`LookupError`</b>: If node op types have not been loaded
|
||||
from partition graphs yet.
|
||||
* <b>`ValueError`</b>: If the node does not exist in partition graphs.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.node_recipients(node_name, is_control=False)` {#DebugDumpDir.node_recipients}
|
||||
|
||||
Get recipient of the given node's output according to partition graphs.
|
||||
|
||||
##### Args:
|
||||
|
||||
|
||||
* <b>`node_name`</b>: (`str`) name of the node.
|
||||
* <b>`is_control`</b>: (`bool`) whether control outputs, rather than non-control
|
||||
outputs, are to be returned.
|
||||
|
||||
##### Returns:
|
||||
|
||||
(`list` of `str`) all inputs to the node, as a list of node names.
|
||||
|
||||
##### Raises:
|
||||
|
||||
|
||||
* <b>`LookupError`</b>: If node inputs and control inputs have not been loaded
|
||||
from partition graphs yet.
|
||||
* <b>`ValueError`</b>: If the node does not exist in partition graphs.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.node_traceback(element_name)` {#DebugDumpDir.node_traceback}
|
||||
|
||||
Try to retrieve the Python traceback of node's construction.
|
||||
|
||||
##### Args:
|
||||
|
||||
|
||||
* <b>`element_name`</b>: (`str`) Name of a graph element (node or tensor).
|
||||
|
||||
##### Returns:
|
||||
|
||||
(list) The traceback list object as returned by the `extract_trace`
|
||||
method of Python's traceback module.
|
||||
|
||||
##### Raises:
|
||||
|
||||
|
||||
* <b>`LookupError`</b>: If Python graph is not available for traceback lookup.
|
||||
* <b>`KeyError`</b>: If the node cannot be found in the Python graph loaded.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.nodes()` {#DebugDumpDir.nodes}
|
||||
|
||||
Get a list of all nodes from the partition graphs.
|
||||
|
||||
##### Returns:
|
||||
|
||||
All nodes' names, as a list of str.
|
||||
|
||||
##### Raises:
|
||||
|
||||
|
||||
* <b>`LookupError`</b>: If no partition graphs have been loaded.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.partition_graphs()` {#DebugDumpDir.partition_graphs}
|
||||
|
||||
Get the partition graphs.
|
||||
|
||||
##### Returns:
|
||||
|
||||
Partition graphs as repeated fields of GraphDef.
|
||||
|
||||
##### Raises:
|
||||
|
||||
|
||||
* <b>`LookupError`</b>: If no partition graphs have been loaded.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.set_python_graph(python_graph)` {#DebugDumpDir.set_python_graph}
|
||||
|
||||
Provide Python `Graph` object to the wrapper.
|
||||
|
||||
Unlike the partition graphs, which are protobuf `GraphDef` objects, `Graph`
|
||||
is a Python object and carries additional information such as the traceback
|
||||
of the construction of the nodes in the graph.
|
||||
|
||||
##### Args:
|
||||
|
||||
|
||||
* <b>`python_graph`</b>: (ops.Graph) The Python Graph object.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.size` {#DebugDumpDir.size}
|
||||
|
||||
Total number of dumped tensors in the dump root directory.
|
||||
|
||||
##### Returns:
|
||||
|
||||
(`int`) total number of dumped tensors in the dump root directory.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.t0` {#DebugDumpDir.t0}
|
||||
|
||||
Absolute timestamp of the first dumped tensor.
|
||||
|
||||
##### Returns:
|
||||
|
||||
(`int`) absolute timestamp of the first dumped tensor, in microseconds.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.transitive_inputs(node_name, include_control=True)` {#DebugDumpDir.transitive_inputs}
|
||||
|
||||
Get the transitive inputs of given node according to partition graphs.
|
||||
|
||||
##### Args:
|
||||
|
||||
|
||||
* <b>`node_name`</b>: Name of the node
|
||||
* <b>`include_control`</b>: Include control inputs (True by default).
|
||||
|
||||
##### Returns:
|
||||
|
||||
(`list` of `str`) all transitive inputs to the node, as a list of node
|
||||
names.
|
||||
|
||||
##### Raises:
|
||||
|
||||
|
||||
* <b>`LookupError`</b>: If node inputs and control inputs have not been loaded
|
||||
from partition graphs yet.
|
||||
* <b>`ValueError`</b>: If the node does not exist in partition graphs.
|
||||
|
||||
|
||||
- - -
|
||||
|
||||
#### `tf_debug.DebugDumpDir.watch_key_to_data(debug_watch_key)` {#DebugDumpDir.watch_key_to_data}
|
||||
|
||||
Get all `DebugTensorDatum` instances corresponding to a debug watch key.
|
||||
|
||||
##### Args:
|
||||
|
||||
|
||||
* <b>`debug_watch_key`</b>: (`str`) debug watch key.
|
||||
|
||||
##### Returns:
|
||||
|
||||
A list of `DebugTensorDatum` instances that correspond to the debug watch
|
||||
key. If the watch key does not exist, returns an empty list.
|
||||
|
||||
##### Raises:
|
||||
|
||||
|
||||
* <b>`ValueError`</b>: If the debug watch key does not exist.
|
||||
|
||||
|
@ -0,0 +1,20 @@
|
||||
### `tf_debug.has_inf_or_nan(datum, tensor)` {#has_inf_or_nan}
|
||||
|
||||
A predicate for whether a tensor consists of any bad numerical values.
|
||||
|
||||
This predicate is common enough to merit definition in this module.
|
||||
Bad numerical values include `nan`s and `inf`s.
|
||||
The signature of this function follows the requirement of the method
|
||||
`DebugDumpDir.find()`.
|
||||
|
||||
##### Args:
|
||||
|
||||
|
||||
* <b>`datum`</b>: (`DebugTensorDatum`) Datum metadata.
|
||||
* <b>`tensor`</b>: (`numpy.ndarray` or None) Value of the tensor. None represents
|
||||
an uninitialized tensor.
|
||||
|
||||
##### Returns:
|
||||
|
||||
(`bool`) True if and only if tensor consists of any nan or inf values.
|
||||
|
@ -0,0 +1,30 @@
|
||||
### `tf_debug.watch_graph(run_options, graph, debug_ops='DebugIdentity', debug_urls=None, node_name_regex_whitelist=None, op_type_regex_whitelist=None)` {#watch_graph}
|
||||
|
||||
Add debug watches to `RunOptions` for a TensorFlow graph.
|
||||
|
||||
To watch all `Tensor`s on the graph, let both `node_name_regex_whitelist`
|
||||
and `op_type_regex_whitelist` be the default (`None`).
|
||||
|
||||
N.B.: Under certain circumstances, not all specified `Tensor`s will be
|
||||
actually watched (e.g., nodes that are constant-folded during runtime will
|
||||
not be watched).
|
||||
|
||||
##### Args:
|
||||
|
||||
|
||||
* <b>`run_options`</b>: An instance of `config_pb2.RunOptions` to be modified.
|
||||
* <b>`graph`</b>: An instance of `ops.Graph`.
|
||||
* <b>`debug_ops`</b>: (`str` or `list` of `str`) name(s) of the debug op(s) to use.
|
||||
* <b>`debug_urls`</b>: URLs to send debug values to. Can be a list of strings,
|
||||
a single string, or None. The case of a single string is equivalent to
|
||||
a list consisting of a single string, e.g., `file:///tmp/tfdbg_dump_1`,
|
||||
`grpc://localhost:12345`.
|
||||
* <b>`node_name_regex_whitelist`</b>: Regular-expression whitelist for node_name,
|
||||
e.g., `"(weight_[0-9]+|bias_.*)"`
|
||||
* <b>`op_type_regex_whitelist`</b>: Regular-expression whitelist for the op type of
|
||||
nodes, e.g., `"(Variable|Add)"`.
|
||||
If both `node_name_regex_whitelist` and `op_type_regex_whitelist`
|
||||
are set, the two filtering operations will occur in a logical `AND`
|
||||
relation. In other words, a node will be included if and only if it
|
||||
hits both whitelists.
|
||||
|
@ -1146,3 +1146,14 @@
|
||||
* [`copy_variable_to_graph`](../../api_docs/python/contrib.copy_graph.md#copy_variable_to_graph)
|
||||
* [`get_copied_op`](../../api_docs/python/contrib.copy_graph.md#get_copied_op)
|
||||
|
||||
* **[TensorFlow Debugger](../../api_docs/python/tf_debug.md)**:
|
||||
* [`add_debug_tensor_watch`](../../api_docs/python/tf_debug.md#add_debug_tensor_watch)
|
||||
* [`DebugDumpDir`](../../api_docs/python/tf_debug.md#DebugDumpDir)
|
||||
* [`DebugTensorDatum`](../../api_docs/python/tf_debug.md#DebugTensorDatum)
|
||||
* [`has_inf_or_nan`](../../api_docs/python/tf_debug.md#has_inf_or_nan)
|
||||
* [`load_tensor_from_event_file`](../../api_docs/python/tf_debug.md#load_tensor_from_event_file)
|
||||
* [`LocalCLIDebugHook`](../../api_docs/python/tf_debug.md#LocalCLIDebugHook)
|
||||
* [`LocalCLIDebugWrapperSession`](../../api_docs/python/tf_debug.md#LocalCLIDebugWrapperSession)
|
||||
* [`watch_graph`](../../api_docs/python/tf_debug.md#watch_graph)
|
||||
* [`watch_graph_with_blacklists`](../../api_docs/python/tf_debug.md#watch_graph_with_blacklists)
|
||||
|
||||
|
1238
tensorflow/g3doc/api_docs/python/tf_debug.md
Normal file
1238
tensorflow/g3doc/api_docs/python/tf_debug.md
Normal file
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Reference in New Issue
Block a user