6fd1b02496
Changes name of folder from tensorflow to tflite-micro and updates docs to reference TensorFlow Lite Micro specifically instead of TensorFlow. Signed-off-by: Lauren Murphy <lauren.murphy@intel.com>
107 lines
4.5 KiB
Python
107 lines
4.5 KiB
Python
# Lint as: python3
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# Copyright 2019 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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# pylint: disable=g-bad-import-order
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"""Load data from the specified paths and format them for training."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import json
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import numpy as np
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import tensorflow as tf
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from data_augmentation import augment_data
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LABEL_NAME = "gesture"
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DATA_NAME = "accel_ms2_xyz"
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class DataLoader(object):
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"""Loads data and prepares for training."""
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def __init__(self, train_data_path, valid_data_path, test_data_path,
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seq_length):
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self.dim = 3
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self.seq_length = seq_length
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self.label2id = {"wing": 0, "ring": 1, "slope": 2, "negative": 3}
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self.train_data, self.train_label, self.train_len = self.get_data_file(
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train_data_path, "train")
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self.valid_data, self.valid_label, self.valid_len = self.get_data_file(
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valid_data_path, "valid")
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self.test_data, self.test_label, self.test_len = self.get_data_file(
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test_data_path, "test")
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def get_data_file(self, data_path, data_type): # pylint: disable=no-self-use
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"""Get train, valid and test data from files."""
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data = []
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label = []
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with open(data_path, "r") as f:
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lines = f.readlines()
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for idx, line in enumerate(lines): # pylint: disable=unused-variable
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dic = json.loads(line)
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data.append(dic[DATA_NAME])
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label.append(dic[LABEL_NAME])
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if data_type == "train":
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data, label = augment_data(data, label)
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length = len(label)
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print(data_type + "_data_length:" + str(length))
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return data, label, length
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def pad(self, data, seq_length, dim): # pylint: disable=no-self-use
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"""Get neighbour padding."""
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noise_level = 20
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padded_data = []
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# Before- Neighbour padding
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tmp_data = (np.random.rand(seq_length, dim) - 0.5) * noise_level + data[0]
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tmp_data[(seq_length -
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min(len(data), seq_length)):] = data[:min(len(data), seq_length)]
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padded_data.append(tmp_data)
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# After- Neighbour padding
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tmp_data = (np.random.rand(seq_length, dim) - 0.5) * noise_level + data[-1]
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tmp_data[:min(len(data), seq_length)] = data[:min(len(data), seq_length)]
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padded_data.append(tmp_data)
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return padded_data
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def format_support_func(self, padded_num, length, data, label):
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"""Support function for format.(Helps format train, valid and test.)"""
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# Add 2 padding, initialize data and label
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length *= padded_num
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features = np.zeros((length, self.seq_length, self.dim))
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labels = np.zeros(length)
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# Get padding for train, valid and test
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for idx, (data, label) in enumerate(zip(data, label)): # pylint: disable=redefined-argument-from-local
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padded_data = self.pad(data, self.seq_length, self.dim)
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for num in range(padded_num):
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features[padded_num * idx + num] = padded_data[num]
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labels[padded_num * idx + num] = self.label2id[label]
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# Turn into tf.data.Dataset
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dataset = tf.data.Dataset.from_tensor_slices(
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(features, labels.astype("int32")))
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return length, dataset
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def format(self):
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"""Format data(including padding, etc.) and get the dataset for the model."""
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padded_num = 2
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self.train_len, self.train_data = self.format_support_func(
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padded_num, self.train_len, self.train_data, self.train_label)
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self.valid_len, self.valid_data = self.format_support_func(
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padded_num, self.valid_len, self.valid_data, self.valid_label)
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self.test_len, self.test_data = self.format_support_func(
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padded_num, self.test_len, self.test_data, self.test_label)
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