# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Exception types for TensorFlow errors."""


import traceback
import warnings

from . import error_codes


# @tf_export("OpError", "errors.OpError")
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.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.OK
# tf_export("errors.OK").export_constant(__name__, "OK")
CANCELLED = error_codes.CANCELLED
# tf_export("errors.CANCELLED").export_constant(__name__, "CANCELLED")
UNKNOWN = error_codes.UNKNOWN
# tf_export("errors.UNKNOWN").export_constant(__name__, "UNKNOWN")
INVALID_ARGUMENT = error_codes.INVALID_ARGUMENT
# tf_export("errors.INVALID_ARGUMENT").export_constant(__name__,
# "INVALID_ARGUMENT")
DEADLINE_EXCEEDED = error_codes.DEADLINE_EXCEEDED
# tf_export("errors.DEADLINE_EXCEEDED").export_constant(__name__,
# "DEADLINE_EXCEEDED")
NOT_FOUND = error_codes.NOT_FOUND
# tf_export("errors.NOT_FOUND").export_constant(__name__, "NOT_FOUND")
ALREADY_EXISTS = error_codes.ALREADY_EXISTS
# tf_export("errors.ALREADY_EXISTS").export_constant(__name__, "ALREADY_EXISTS")
PERMISSION_DENIED = error_codes.PERMISSION_DENIED
# tf_export("errors.PERMISSION_DENIED").export_constant(__name__,
# "PERMISSION_DENIED")
UNAUTHENTICATED = error_codes.UNAUTHENTICATED
# tf_export("errors.UNAUTHENTICATED").export_constant(__name__, "UNAUTHENTICATED")
RESOURCE_EXHAUSTED = error_codes.RESOURCE_EXHAUSTED
# tf_export("errors.RESOURCE_EXHAUSTED").export_constant(__name__,
# "RESOURCE_EXHAUSTED")
FAILED_PRECONDITION = error_codes.FAILED_PRECONDITION
# tf_export("errors.FAILED_PRECONDITION").export_constant(__name__,
# "FAILED_PRECONDITION")
ABORTED = error_codes.ABORTED
# tf_export("errors.ABORTED").export_constant(__name__, "ABORTED")
OUT_OF_RANGE = error_codes.OUT_OF_RANGE
# tf_export("errors.OUT_OF_RANGE").export_constant(__name__, "OUT_OF_RANGE")
UNIMPLEMENTED = error_codes.UNIMPLEMENTED
# tf_export("errors.UNIMPLEMENTED").export_constant(__name__, "UNIMPLEMENTED")
INTERNAL = error_codes.INTERNAL
# tf_export("errors.INTERNAL").export_constant(__name__, "INTERNAL")
UNAVAILABLE = error_codes.UNAVAILABLE
# tf_export("errors.UNAVAILABLE").export_constant(__name__, "UNAVAILABLE")
DATA_LOSS = error_codes.DATA_LOSS
# tf_export("errors.DATA_LOSS").export_constant(__name__, "DATA_LOSS")


# @tf_export("errors.CancelledError")
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)


# @tf_export("errors.UnknownError")
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)


# @tf_export("errors.InvalidArgumentError")
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
        )


# @tf_export("errors.DeadlineExceededError")
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
        )


# @tf_export("errors.NotFoundError")
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)


# @tf_export("errors.AlreadyExistsError")
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
        )


# @tf_export("errors.PermissionDeniedError")
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
        )


# @tf_export("errors.UnauthenticatedError")
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
        )


# @tf_export("errors.ResourceExhaustedError")
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
        )


# @tf_export("errors.FailedPreconditionError")
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
        )


# @tf_export("errors.AbortedError")
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)


# @tf_export("errors.OutOfRangeError")
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
        )


# @tf_export("errors.UnimplementedError")
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
        )


# @tf_export("errors.InternalError")
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)


# @tf_export("errors.UnavailableError")
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
        )


# @tf_export("errors.DataLossError")
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())
)


# @tf_export("errors.exception_type_from_error_code")
def exception_type_from_error_code(error_code):
    return _CODE_TO_EXCEPTION_CLASS[error_code]


# @tf_export("errors.error_code_from_exception_type")
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)


# Named like a function for backwards compatibility with the
# @tf_contextlib.contextmanager version, which was switched to a class to avoid
# some object creation overhead.
# TODO(b/77295559): expand use of TF_Status* SWIG typemap and deprecate this.
# @tf_export("errors.raise_exception_on_not_ok_status")  # pylint: disable=invalid-name
class raise_exception_on_not_ok_status(object):
    """Context manager to check for C API status."""

    def __enter__(self):
        return "Status not OK"

    def __exit__(self, type_arg, value_arg, traceback_arg):
        return False  # False values do not suppress exceptions
