Python BenchmarkUtilの例

コード例 #1

def get_butil(name):
    if len(sys.argv) <= 1:
        sys.argv.append('cpu')
    USE_GPU = True if sys.argv[1] == 'gpu' else False
    os.environ["CUDA_VISIBLE_DEVICES"] = "0" if USE_GPU else ""

    return BenchmarkUtil(model_name=name.split('/')[-1].split('.')[0] + ' {}'.format(sys.argv[1]),
                         stats_save_path='/tmp/stats/',
                         monitors=[CPUMonitor, MemoryMonitor, GPUMonitor])

コード例 #2

"""

import os
import sys
import json

if len(sys.argv) <= 1:
    sys.argv.append('cpu')
USE_GPU = True if sys.argv[1] == 'gpu' else False
os.environ["CUDA_VISIBLE_DEVICES"] = "0" if USE_GPU else ""

from benchmark.benchmark import BenchmarkUtil
from benchmark.system_monitors import CPUMonitor, MemoryMonitor, GPUMonitor

butil = BenchmarkUtil(
    model_name='EP11 Reinitializable_iterator_switch {}'.format(sys.argv[1]),
    stats_save_path='/tmp/stats/',
    monitors=[CPUMonitor, MemoryMonitor, GPUMonitor])


@butil.monitor
def main():
    # Imports
    import tensorflow as tf
    from tensorflow.examples.tutorials.mnist import input_data
    import time

    # Global Variables
    EPOCH = 100
    BATCH_SIZE = 32
    DISPLAY_STEP = 1

コード例 #3

ファイル: EP3_Feedable_Dataset.py プロジェクト: kingspp/tensorflow-dataset-api

"""
import os
import sys
import json
import time

if len(sys.argv) <= 1:
    sys.argv.append('cpu')
USE_GPU = True if sys.argv[1] == 'gpu' else False
os.environ["CUDA_VISIBLE_DEVICES"] = "0" if USE_GPU else ""

from benchmark.benchmark import BenchmarkUtil
from benchmark.system_monitors import CPUMonitor, MemoryMonitor, GPUMonitor

butil = BenchmarkUtil(model_name='EP3 Feedable Dataset {}'.format(sys.argv[1]),
                      stats_save_path='/tmp/stats/',
                      monitors=[CPUMonitor, MemoryMonitor, GPUMonitor])


@butil.monitor
def main():
    # Imports
    import tensorflow as tf
    from tensorflow.examples.tutorials.mnist import input_data

    # Global Variables
    EPOCH = 100
    BATCH_SIZE = 32
    DISPLAY_STEP = 1

    mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)

コード例 #4

..todo::
"""
import os
import sys
import json

if len(sys.argv) <= 1:
    sys.argv.append('cpu')
USE_GPU = True if sys.argv[1] == 'gpu' else False
os.environ["CUDA_VISIBLE_DEVICES"] = "0" if USE_GPU else ""

from benchmark.benchmark import BenchmarkUtil
from benchmark.system_monitors import CPUMonitor, MemoryMonitor, GPUMonitor

butil = BenchmarkUtil(model_name='EP1 Basic Placeholder {}'.format(
    sys.argv[1]),
                      stats_save_path='/tmp/stats/',
                      monitors=[CPUMonitor, MemoryMonitor, GPUMonitor])


@butil.monitor
def main():
    # Imports
    import tensorflow as tf
    from tensorflow.examples.tutorials.mnist import input_data
    import time

    # Global Variables
    EPOCH = 100
    BATCH_SIZE = 32
    DISPLAY_STEP = 1

コード例 #5

ファイル: EP19_Feedable_Iterator_FetchOP.py プロジェクト: kingspp/tensorflow-dataset-api

"""
import os
import sys
import json
import time

if len(sys.argv) <= 1:
    sys.argv.append('cpu')
USE_GPU = True if sys.argv[1] == 'gpu' else False
os.environ["CUDA_VISIBLE_DEVICES"] = "0" if USE_GPU else ""

from benchmark.benchmark import BenchmarkUtil
from benchmark.system_monitors import CPUMonitor, MemoryMonitor, GPUMonitor

butil = BenchmarkUtil(model_name='EP19 Feedable Iterator Fetch OP {}'.format(
    sys.argv[1]),
                      stats_save_path='/tmp/stats/',
                      monitors=[CPUMonitor, MemoryMonitor, GPUMonitor])


@butil.monitor
def main():
    # Imports
    import tensorflow as tf
    from tensorflow.examples.tutorials.mnist import input_data

    # Global Variables
    EPOCH = 100
    BATCH_SIZE = 32
    DISPLAY_STEP = 1

    mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)

コード例 #6

ファイル: EP15_Feedable_Iterator_Multiple_Dataset_Initializable_Iterator.py プロジェクト: kingspp/tensorflow-dataset-api

import sys
import time
import json

if len(sys.argv) <= 1:
    sys.argv.append('cpu')
USE_GPU = True if sys.argv[1] == 'gpu' else False
os.environ["CUDA_VISIBLE_DEVICES"] = "0" if USE_GPU else ""

from benchmark.benchmark import BenchmarkUtil
from benchmark.system_monitors import CPUMonitor, MemoryMonitor, GPUMonitor
import random

butil = BenchmarkUtil(
    model_name=
    'EP15 Feedable Iterator Multiple Dataset Initializable Iterator {}'.format(
        sys.argv[1]),
    stats_save_path='/tmp/stats/',
    monitors=[CPUMonitor, MemoryMonitor, GPUMonitor])


# @butil.monitor
def main():
    # Imports
    import tensorflow as tf
    from tensorflow.examples.tutorials.mnist import input_data

    # Global Variables
    EPOCH = 100
    BATCH_SIZE = 32
    bs_placeholder = tf.placeholder(dtype=tf.int64)
    DISPLAY_STEP = 1

コード例 #7

ファイル: EP1_Basic_Placeholders.py プロジェクト: himaprasoonpt/tensorflow-dataset-api

| **@version:** v0.0.1
|
| **Description:**
| Basic Placeholders
| **Sphinx Documentation Status:** Complete
|
..todo::
"""
import os

os.environ["CUDA_VISIBLE_DEVICES"] = "0"
from benchmark.benchmark import BenchmarkUtil
from benchmark.system_monitors import CPUMonitor, MemoryMonitor, GPUMonitor

butil = BenchmarkUtil(model_name='Basic Placeholder',
                      stats_save_path='/tmp/stats/',
                      monitors=[CPUMonitor, MemoryMonitor, GPUMonitor])


@butil.monitor
def main():
    # Imports
    import tensorflow as tf
    from tensorflow.examples.tutorials.mnist import input_data
    import time

    start = time.time()

    # Global Variables
    EPOCH = 1
    BATCH_SIZE = 32

コード例 #8

ファイル: EP12_Dataset_inbuilt_epoch.py プロジェクト: kingspp/tensorflow-dataset-api

# Imports
import os
import sys

if len(sys.argv) <= 1:
    sys.argv.append('cpu')
USE_GPU = True if sys.argv[1] == 'gpu' else False
os.environ["CUDA_VISIBLE_DEVICES"] = "0" if USE_GPU else ""

from benchmark.benchmark import BenchmarkUtil
from benchmark.system_monitors import CPUMonitor, MemoryMonitor, GPUMonitor

butil = BenchmarkUtil(model_name='EP12 Dataset Inbuilt Epoch {}'.format(
    sys.argv[1]),
                      stats_save_path='/tmp/stats/',
                      monitors=[CPUMonitor, MemoryMonitor, GPUMonitor])


@butil.monitor
def main():
    # Imports
    import tensorflow as tf
    from tensorflow.examples.tutorials.mnist import input_data
    import time

    start = time.time()
    # Global Variables
    EPOCH = 100
    BATCH_SIZE = 32

    mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)

コード例 #9

|
| **Description:**
| 
|
| **Sphinx Documentation Status:** --
|
..todo::
"""

import os

os.environ["CUDA_VISIBLE_DEVICES"] = "0"
from benchmark.benchmark import BenchmarkUtil
from benchmark.system_monitors import CPUMonitor, MemoryMonitor, GPUMonitor

butil = BenchmarkUtil(model_name='Reinitializable Iterator', stats_save_path='/tmp/stats/',
                      monitors=[CPUMonitor, MemoryMonitor, GPUMonitor])


@butil.monitor
def main():
    # Imports
    import tensorflow as tf
    from tensorflow.examples.tutorials.mnist import input_data
    import time

    start = time.time()

    # Global Variables
    EPOCH = 100
    BATCH_SIZE = 32
    DISPLAY_STEP = 1

コード例 #10

|
| **Description:**
| Feedable Dataset
|
| **Sphinx Documentation Status:** Complete
|
..todo::
"""
import os

os.environ["CUDA_VISIBLE_DEVICES"] = "0"
from benchmark.benchmark import BenchmarkUtil
from benchmark.system_monitors import CPUMonitor, MemoryMonitor, GPUMonitor

butil = BenchmarkUtil(model_name='Feedable Dataset',
                      stats_save_path='/tmp/stats/',
                      monitors=[CPUMonitor, MemoryMonitor, GPUMonitor])


@butil.monitor
def main():
    # Imports
    import tensorflow as tf
    from tensorflow.examples.tutorials.mnist import input_data
    import time

    start = time.time()

    # Global Variables
    EPOCH = 100
    BATCH_SIZE = 32