TensorFlow定义错误的异常类型(详细)

由 Carrie 创建, 最后一次修改 2017-09-08

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"" TensorFlow错误的异常类型.""

from __future__ import absolute_import from __future__ import division from __future__ import print_function import contextlib import traceback import warnings from tensorflow.core.lib.core import error_codes_pb2 from tensorflow.python import pywrap_tensorflow from tensorflow.python.util import compat class OpError(Exception): """A generic error that is raised when TensorFlow execution fails. Whenever possible, the session will raise a more specific subclass of `OpError` from the `tf.errors` module. """ def __init__(self, node_def, op, message, error_code): """Creates a new `OpError` indicating that a particular op failed. Args: node_def: The `node_def_pb2.NodeDef` proto representing the op that failed, if known; otherwise None. op: The `ops.Operation` that failed, if known; otherwise None. message: The message string describing the failure. error_code: The `error_codes_pb2.Code` describing the error. """ super(OpError, self).__init__() self._message = message self._node_def = node_def self._op = op self._error_code = error_code @property def message(self): """The error message that describes the error.""" return self._message @property def op(self): """The operation that failed, if known. *N.B.* If the failed op was synthesized at runtime, e.g. a `Send` or `Recv` op, there will be no corresponding @{tf.Operation} object. In that case, this will return `None`, and you should instead use the @{tf.OpError.node_def} to discover information about the op. Returns: The `Operation` that failed, or None. """ return self._op @property def error_code(self): """The integer error code that describes the error.""" return self._error_code @property def node_def(self): """The `NodeDef` proto representing the op that failed.""" return self._node_def def __str__(self): if self._op is not None: output = ["%s\n\nCaused by op %r, defined at:\n" % (self.message, self._op.name,)] curr_traceback_list = traceback.format_list(self._op.traceback) output.extend(curr_traceback_list) # pylint: disable=protected-access original_op = self._op._original_op # pylint: enable=protected-access while original_op is not None: output.append( "\n...which was originally created as op %r, defined at:\n" % (original_op.name,)) prev_traceback_list = curr_traceback_list curr_traceback_list = traceback.format_list(original_op.traceback) # Attempt to elide large common subsequences of the subsequent # stack traces. # # TODO(mrry): Consider computing the actual longest common subsequence. is_eliding = False elide_count = 0 last_elided_line = None for line, line_in_prev in zip(curr_traceback_list, prev_traceback_list): if line == line_in_prev: if is_eliding: elide_count += 1 last_elided_line = line else: output.append(line) is_eliding = True elide_count = 0 else: if is_eliding: if elide_count > 0: output.extend( ["[elided %d identical lines from previous traceback]\n" % (elide_count - 1,), last_elided_line]) is_eliding = False output.extend(line) # pylint: disable=protected-access original_op = original_op._original_op # pylint: enable=protected-access output.append("\n%s (see above for traceback): %s\n" % (type(self).__name__, self.message)) return "".join(output) else: return self.message OK = error_codes_pb2.OK CANCELLED = error_codes_pb2.CANCELLED UNKNOWN = error_codes_pb2.UNKNOWN INVALID_ARGUMENT = error_codes_pb2.INVALID_ARGUMENT DEADLINE_EXCEEDED = error_codes_pb2.DEADLINE_EXCEEDED NOT_FOUND = error_codes_pb2.NOT_FOUND ALREADY_EXISTS = error_codes_pb2.ALREADY_EXISTS PERMISSION_DENIED = error_codes_pb2.PERMISSION_DENIED UNAUTHENTICATED = error_codes_pb2.UNAUTHENTICATED RESOURCE_EXHAUSTED = error_codes_pb2.RESOURCE_EXHAUSTED FAILED_PRECONDITION = error_codes_pb2.FAILED_PRECONDITION ABORTED = error_codes_pb2.ABORTED OUT_OF_RANGE = error_codes_pb2.OUT_OF_RANGE UNIMPLEMENTED = error_codes_pb2.UNIMPLEMENTED INTERNAL = error_codes_pb2.INTERNAL UNAVAILABLE = error_codes_pb2.UNAVAILABLE DATA_LOSS = error_codes_pb2.DATA_LOSS # pylint: disable=line-too-long class CancelledError(OpError): """Raised when an operation or step is cancelled. For example, a long-running operation (e.g. @{tf.QueueBase.enqueue} may be cancelled by running another operation (e.g. @{tf.QueueBase.close}, or by @{tf.Session.close}. A step that is running such a long-running operation will fail by raising `CancelledError`. @@__init__ """ def __init__(self, node_def, op, message): """Creates a `CancelledError`.""" super(CancelledError, self).__init__(node_def, op, message, CANCELLED) # pylint: enable=line-too-long class UnknownError(OpError): """Unknown error. An example of where this error may be returned is if a Status value received from another address space belongs to an error-space that is not known to this address space. Also errors raised by APIs that do not return enough error information may be converted to this error. @@__init__ """ def __init__(self, node_def, op, message, error_code=UNKNOWN): """Creates an `UnknownError`.""" super(UnknownError, self).__init__(node_def, op, message, error_code) class InvalidArgumentError(OpError): """Raised when an operation receives an invalid argument. This may occur, for example, if an operation is receives an input tensor that has an invalid value or shape. For example, the @{tf.matmul} op will raise this error if it receives an input that is not a matrix, and the @{tf.reshape} op will raise this error if the new shape does not match the number of elements in the input tensor. @@__init__ """ def __init__(self, node_def, op, message): """Creates an `InvalidArgumentError`.""" super(InvalidArgumentError, self).__init__(node_def, op, message, INVALID_ARGUMENT) class DeadlineExceededError(OpError): """Raised when a deadline expires before an operation could complete. This exception is not currently used. @@__init__ """ def __init__(self, node_def, op, message): """Creates a `DeadlineExceededError`.""" super(DeadlineExceededError, self).__init__(node_def, op, message, DEADLINE_EXCEEDED) class NotFoundError(OpError): """Raised when a requested entity (e.g., a file or directory) was not found. For example, running the @{tf.WholeFileReader.read} operation could raise `NotFoundError` if it receives the name of a file that does not exist. @@__init__ """ def __init__(self, node_def, op, message): """Creates a `NotFoundError`.""" super(NotFoundError, self).__init__(node_def, op, message, NOT_FOUND) class AlreadyExistsError(OpError): """Raised when an entity that we attempted to create already exists. For example, running an operation that saves a file (e.g. @{tf.train.Saver.save}) could potentially raise this exception if an explicit filename for an existing file was passed. @@__init__ """ def __init__(self, node_def, op, message): """Creates an `AlreadyExistsError`.""" super(AlreadyExistsError, self).__init__(node_def, op, message, ALREADY_EXISTS) class PermissionDeniedError(OpError): """Raised when the caller does not have permission to run an operation. For example, running the @{tf.WholeFileReader.read} operation could raise `PermissionDeniedError` if it receives the name of a file for which the user does not have the read file permission. @@__init__ """ def __init__(self, node_def, op, message): """Creates a `PermissionDeniedError`.""" super(PermissionDeniedError, self).__init__(node_def, op, message, PERMISSION_DENIED) class UnauthenticatedError(OpError): """The request does not have valid authentication credentials. This exception is not currently used. @@__init__ """ def __init__(self, node_def, op, message): """Creates an `UnauthenticatedError`.""" super(UnauthenticatedError, self).__init__(node_def, op, message, UNAUTHENTICATED) class ResourceExhaustedError(OpError): """Some resource has been exhausted. For example, this error might be raised if a per-user quota is exhausted, or perhaps the entire file system is out of space. @@__init__ """ def __init__(self, node_def, op, message): """Creates a `ResourceExhaustedError`.""" super(ResourceExhaustedError, self).__init__(node_def, op, message, RESOURCE_EXHAUSTED) class FailedPreconditionError(OpError): """Operation was rejected because the system is not in a state to execute it. This exception is most commonly raised when running an operation that reads a @{tf.Variable} before it has been initialized. @@__init__ """ def __init__(self, node_def, op, message): """Creates a `FailedPreconditionError`.""" super(FailedPreconditionError, self).__init__(node_def, op, message, FAILED_PRECONDITION) class AbortedError(OpError): """The operation was aborted, typically due to a concurrent action. For example, running a @{tf.QueueBase.enqueue} operation may raise `AbortedError` if a @{tf.QueueBase.close} operation previously ran. @@__init__ """ def __init__(self, node_def, op, message): """Creates an `AbortedError`.""" super(AbortedError, self).__init__(node_def, op, message, ABORTED) class OutOfRangeError(OpError): """Raised when an operation iterates past the valid input range. This exception is raised in "end-of-file" conditions, such as when a @{tf.QueueBase.dequeue} operation is blocked on an empty queue, and a @{tf.QueueBase.close} operation executes. @@__init__ """ def __init__(self, node_def, op, message): """Creates an `OutOfRangeError`.""" super(OutOfRangeError, self).__init__(node_def, op, message, OUT_OF_RANGE) class UnimplementedError(OpError): """Raised when an operation has not been implemented. Some operations may raise this error when passed otherwise-valid arguments that it does not currently support. For example, running the @{tf.nn.max_pool} operation would raise this error if pooling was requested on the batch dimension, because this is not yet supported. @@__init__ """ def __init__(self, node_def, op, message): """Creates an `UnimplementedError`.""" super(UnimplementedError, self).__init__(node_def, op, message, UNIMPLEMENTED) class InternalError(OpError): """Raised when the system experiences an internal error. This exception is raised when some invariant expected by the runtime has been broken. Catching this exception is not recommended. @@__init__ """ def __init__(self, node_def, op, message): """Creates an `InternalError`.""" super(InternalError, self).__init__(node_def, op, message, INTERNAL) class UnavailableError(OpError): """Raised when the runtime is currently unavailable. This exception is not currently used. @@__init__ """ def __init__(self, node_def, op, message): """Creates an `UnavailableError`.""" super(UnavailableError, self).__init__(node_def, op, message, UNAVAILABLE) class DataLossError(OpError): """Raised when unrecoverable data loss or corruption is encountered. For example, this may be raised by running a @{tf.WholeFileReader.read} operation, if the file is truncated while it is being read. @@__init__ """ def __init__(self, node_def, op, message): """Creates a `DataLossError`.""" super(DataLossError, self).__init__(node_def, op, message, DATA_LOSS) _CODE_TO_EXCEPTION_CLASS = { CANCELLED: CancelledError, UNKNOWN: UnknownError, INVALID_ARGUMENT: InvalidArgumentError, DEADLINE_EXCEEDED: DeadlineExceededError, NOT_FOUND: NotFoundError, ALREADY_EXISTS: AlreadyExistsError, PERMISSION_DENIED: PermissionDeniedError, UNAUTHENTICATED: UnauthenticatedError, RESOURCE_EXHAUSTED: ResourceExhaustedError, FAILED_PRECONDITION: FailedPreconditionError, ABORTED: AbortedError, OUT_OF_RANGE: OutOfRangeError, UNIMPLEMENTED: UnimplementedError, INTERNAL: InternalError, UNAVAILABLE: UnavailableError, DATA_LOSS: DataLossError, } _EXCEPTION_CLASS_TO_CODE = dict(( (class_, code) for (code, class_) in _CODE_TO_EXCEPTION_CLASS.items())) def exception_type_from_error_code(error_code): return _CODE_TO_EXCEPTION_CLASS[error_code] def error_code_from_exception_type(cls): return _EXCEPTION_CLASS_TO_CODE[cls] def _make_specific_exception(node_def, op, message, error_code): try: exc_type = exception_type_from_error_code(error_code) return exc_type(node_def, op, message) except KeyError: warnings.warn("Unknown error code: %d" % error_code) return UnknownError(node_def, op, message, error_code) @contextlib.contextmanager def raise_exception_on_not_ok_status(): status = pywrap_tensorflow.TF_NewStatus() try: yield status if pywrap_tensorflow.TF_GetCode(status) != 0: raise _make_specific_exception( None, None, compat.as_text(pywrap_tensorflow.TF_Message(status)), pywrap_tensorflow.TF_GetCode(status)) finally: pywrap_tensorflow.TF_DeleteStatus(status)
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