本文整理汇总了Python中tensorflow.parse_csv方法的典型用法代码示例。如果您正苦于以下问题：Python tensorflow.parse_csv方法的具体用法？Python tensorflow.parse_csv怎么用？Python tensorflow.parse_csv使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类tensorflow的用法示例。
在下文中一共展示了tensorflow.parse_csv方法的5个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: eval_input_fn
# 需要导入模块: import tensorflow [as 别名]
# 或者: from tensorflow import parse_csv [as 别名]
def eval_input_fn(features, labels, batch_size):
"""An input function for evaluation or prediction"""
features=dict(features)
if labels is None:
# No labels, use only features.
inputs = features
else:
inputs = (features, labels)
# Convert the inputs to a Dataset.
dataset = tf.data.Dataset.from_tensor_slices(inputs)
# Batch the examples
assert batch_size is not None, "batch_size must not be None"
dataset = dataset.batch(batch_size)
# Return the dataset.
return dataset
# The remainder of this file contains a simple example of a csv parser,
# implemented using a the `Dataset` class.
# `tf.parse_csv` sets the types of the outputs to match the examples given in
# the `record_defaults` argument. 示例2: eval_input_fn
# 需要导入模块: import tensorflow [as 别名]
# 或者: from tensorflow import parse_csv [as 别名]
def eval_input_fn(features, labels, batch_size):
"""An input function for evaluation or prediction"""
features=dict(features)
if labels is None:
# No labels, use only features.
inputs = features
else:
inputs = (features, labels)
# Convert the inputs to a Dataset.
dataset = tf.data.Dataset.from_tensor_slices(inputs)
# Batch the examples
assert batch_size is not None, "batch_size must not be None"
dataset = dataset.batch(batch_size)
# Return the read end of the pipeline.
return dataset.make_one_shot_iterator().get_next()
# The remainder of this file contains a simple example of a csv parser,
# implemented using a the `Dataset` class.
# `tf.parse_csv` sets the types of the outputs to match the examples given in
# the `record_defaults` argument. 示例3: load_data
# 需要导入模块: import tensorflow [as 别名]
# 或者: from tensorflow import parse_csv [as 别名]
def load_data(y_name='Species'):
"""Returns the iris dataset as (train_x, train_y), (test_x, test_y)."""
train_path, test_path = maybe_download()
train = pd.read_csv(train_path, names=CSV_COLUMN_NAMES, header=0)
train_x, train_y = train, train.pop(y_name)
test = pd.read_csv(test_path, names=CSV_COLUMN_NAMES, header=0)
test_x, test_y = test, test.pop(y_name)
return (train_x, train_y), (test_x, test_y)
# The remainder of this file contains a simple example of a csv parser,
# implemented using a the `Dataset` class.
# `tf.parse_csv` sets the types of the outputs to match the examples given in
# the `record_defaults` argument. 示例4: eval_input_fn
# 需要导入模块: import tensorflow [as 别名]
# 或者: from tensorflow import parse_csv [as 别名]
def eval_input_fn(features, labels, batch_size):
"""An input function for evaluation or prediction"""
features=dict(features)
if labels is None:
# No labels, use only features.
inputs = features
else:
inputs = (features, labels)
# Convert the inputs to a Dataset.
dataset = tf.data.Dataset.from_tensor_slices(inputs)
# Batch the examples
assert batch_size is not None, "batch_size must not be None"
dataset = dataset.batch(batch_size)
# Return the dataset.
return dataset
# The remainder of this file contains a simple example of a csv parser,
# implemented using the `Dataset` class.
# `tf.parse_csv` sets the types of the outputs to match the examples given in
# the `record_defaults` argument. 开发者ID:ShivangShekhar，项目名称:Live-feed-object-device-identification-using-Tensorflow-and-OpenCV，代码行数:27，代码来源:iris_data.py
示例5: eval_input_fn
# 需要导入模块: import tensorflow [as 别名]
# 或者: from tensorflow import parse_csv [as 别名]
def eval_input_fn(features, labels, batch_size):
"""An input function for evaluation or prediction"""
features = dict(features)
if labels is None:
# No labels, use only features.
inputs = features
else:
inputs = (features, labels)
# Convert the inputs to a Dataset.
dataset = tf.data.Dataset.from_tensor_slices(inputs)
# Batch the examples
assert batch_size is not None, "batch_size must not be None"
dataset = dataset.batch(batch_size)
# Return the dataset.
return dataset
# The remainder of this file contains a simple example of a csv parser,
# implemented using the `Dataset` class.
# `tf.parse_csv` sets the types of the outputs to match the examples given in
# the `record_defaults` argument.