35 lines
1.1 KiB
Python
35 lines
1.1 KiB
Python
from pathlib import Path
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from typing import List, Tuple
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import tensorflow as tf
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from src.common import DataType, Op
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from src.tf_2.base import TFBase
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class DenseModel(tf.keras.Model):
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def __init__(self, input_dim: int, dtype=tf.DType):
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super().__init__()
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self.dense = tf.keras.layers.Dense(input_dim, dtype=dtype)
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def call(self, input_tensor: tf.Tensor) -> tf.Tensor:
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return self.dense(input_tensor)
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class TFNNDenseBench(TFBase):
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def __init__(self, output_path: Path, data_type: DataType):
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super().__init__(output_path, Op.NN_DENSE, data_type)
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self.tensor: tf.Tensor = None
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self.network: tf.keras.Model = None
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def pre_experiment(self, experiment_args: Tuple[int, int]):
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batch_size, dimension = experiment_args
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with self.device:
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self.tensor = tf.ones((batch_size, dimension), dtype=self.dtype)
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self.network = DenseModel(dimension, self.dtype)
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def experiment(self):
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self.network(self.tensor)
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def run(self, experiment_args: List[Tuple[int, int]], experiment_count: int):
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super().run(experiment_args, experiment_count)
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