<commit_before>from typing import Callable, Tuple, Any, TypeVar

from ..model import Model
from ..shims import TensorFlowShim
from ..util import xp2tensorflow, tensorflow2xp, assert_tensorflow_installed
from ..util import is_tensorflow_array, convert_recursive, is_xp_array
from ..types import Array, ArgsKwargs

try:
    import tensorflow as tf
except ImportError:
    pass

InT = TypeVar("InT")
OutT = TypeVar("OutT")


def TensorFlowWrapper(tensorflow_model, build_model: bool = True) -> Model:
    """Wrap a TensorFlow model, so that it has the same API as Thinc models.
    To optimize the model, you'll need to create a TensorFlow optimizer and call
    optimizer.apply_gradients after each batch.
    """
    assert_tensorflow_installed()
    if not isinstance(tensorflow_model, tf.keras.models.Model):
        err = f"Expected tf.keras.models.Model, got: {type(tensorflow_model)}"
        raise ValueError(err)
    # Building a keras model checks for errors like not specifying an input_shape
    # which can cause other errors in methods like from_disk and from_bytes.
    if build_model:
        tensorflow_model.build()
    return Model("tensorflow", forward, shims=[TensorFlowShim(tensorflow_model)])


def forward(model: Model, X: Array, is_train: bool) -> Tuple[Array, Callable]:
    """Return the output of the wrapped TensorFlow model for the given input,
    along with a callback to handle the backward pass.
    """
    tensorflow_model = model.shims[0]
    X_tensorflow, get_dX = _convert_inputs(model, X, is_train)
    if is_train:
        Y_tensorflow, tensorflow_backprop = tensorflow_model(X_tensorflow, is_train)
    else:
        Y_tensorflow = tensorflow_model(X_tensorflow, is_train)
    Y, get_dY_tensorflow = _convert_outputs(model, Y_tensorflow, is_train)

    def backprop(dY: OutT) -> InT:<commit_msg>cleanup from review<commit_after>from typing import Callable, Tuple, TypeVar

from ..model import Model
from ..shims import TensorFlowShim
from ..util import xp2tensorflow, tensorflow2xp, assert_tensorflow_installed
from ..util import is_tensorflow_array, convert_recursive, is_xp_array
from ..types import ArgsKwargs

try:
    import tensorflow as tf
except ImportError:
    pass

InT = TypeVar("InT")
OutT = TypeVar("OutT")


def TensorFlowWrapper(tensorflow_model, build_model: bool = True) -> Model:
    """Wrap a TensorFlow model, so that it has the same API as Thinc models.
    To optimize the model, you'll need to create a TensorFlow optimizer and call
    optimizer.apply_gradients after each batch.
    """
    assert_tensorflow_installed()
    if not isinstance(tensorflow_model, tf.keras.models.Model):
        err = f"Expected tf.keras.models.Model, got: {type(tensorflow_model)}"
        raise ValueError(err)
    # Building a keras model checks for errors like not specifying an input_shape
    # which can cause other errors in methods like from_disk and from_bytes.
    if build_model:
        tensorflow_model.build()
    return Model("tensorflow", forward, shims=[TensorFlowShim(tensorflow_model)])


def forward(model: Model[InT, OutT], X: InT, is_train: bool) -> Tuple[OutT, Callable]:
    """Return the output of the wrapped TensorFlow model for the given input,
    along with a callback to handle the backward pass.
    """
    tensorflow_model = model.shims[0]
    X_tensorflow, get_dX = _convert_inputs(model, X, is_train)
    if is_train:
        Y_tensorflow, tensorflow_backprop = tensorflow_model(X_tensorflow, is_train)
    else:
        Y_tensorflow = tensorflow_model(X_tensorflow, is_train)
    Y, get_dY_tensorflow = _convert_outputs(model, Y_tensorflow, is_train)

    def backprop(dY: OutT) -> InT:
{'fraction_non_alphanumeric': 0.08092643051771117, 'fraction_numerical': 0.0016348773841961854, 'mean_word_length': 4.19971671388102, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 9, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '3378102', 'n_tokens_mistral': 1133, 'n_tokens_neox': 1118, 'n_words': 358}