import copy
import json
import tensorflow as tf
import numpy as np
from overrides import overrides
from deeppavlov.core.models.nn_model import NNModel
from deeppavlov.core.common.registry import register
from deeppavlov.core.common.log import get_logger
from deeppavlov.core.commands.utils import expand_path
from deeppavlov.models.elmo.bilm_model import LanguageModel
from deeppavlov.models.elmo.train_utils import average_gradients, clip_grads, safely_str2int, dump_weights
from deeppavlov.models.elmo.elmo2tfhub import export2hub
log = get_logger(__name__)
@register('elmo_model')
class ELMo(NNModel):
"""
The :class:`~deeppavlov.models.elmo.elmo.ELMo` is a deep contextualized word representation that models both
complex characteristics of word use (e.g., syntax and semantics), and how these uses vary across linguistic
contexts (i.e., to model polysemy).
You can use this component for LM training, fine tuning, dumping ELMo to a hdf5 file and wrapping it to
the tensorflow hub.
Parameters:
options_json_path: Path to the json configure.
# limitations under the License.
from typing import List, Tuple, Union
import numpy as np
from scipy.sparse import vstack, csr_matrix
from scipy.sparse.linalg import norm as sparse_norm
from deeppavlov.core.common.registry import register
from deeppavlov.core.common.log import get_logger
from deeppavlov.core.models.estimator import Estimator
from deeppavlov.core.common.file import save_pickle
from deeppavlov.core.common.file import load_pickle
from deeppavlov.core.models.serializable import Serializable
logger = get_logger(__name__)
@register("cos_sim_classifier")
class CosineSimilarityClassifier(Estimator, Serializable):
"""
Classifier based on cosine similarity between vectorized sentences
Parameters:
save_path: path to save the model
load_path: path to load the model
"""
def __init__(self,
top_n: int = 1,
save_path: str = None,
load_path: str = None,
