Remove unused GPU usage tools

bin/gpu_usage_chart

@@ -1,5 +0,0 @@
-#!/usr/bin/env python
-from deepspeech_training.util.gpu_usage import GPUUsage
-
-gu = GPUUsage()
-gu.start()

bin/gpu_usage_plot

@@ -1,6 +0,0 @@
-#!/usr/bin/env python
-import sys
-
-from deepspeech_training.util.gpu_usage import GPUUsageChart
-
-GPUUsageChart(sys.argv[1], sys.argv[2])

training/deepspeech_training/util/gpu_usage.py

@@ -1,159 +0,0 @@
-# -*- coding: utf-8 -*-
-
-from __future__ import unicode_literals
-from __future__ import print_function
-from __future__ import absolute_import
-
-import os
-import subprocess
-import csv
-
-from threading import Thread
-from time import time
-from scipy.interpolate import spline
-
-from six.moves import range
-# Do this to be able to use without X
-import matplotlib as mpl
-mpl.use('Agg')
-import matplotlib.pyplot as plt
-import numpy as np
-
-class GPUUsage(Thread):
-    def __init__(self, csvfile=None):
-        super(GPUUsage, self).__init__()
-
-        self._cmd        = [ 'nvidia-smi', 'dmon', '-d', '1', '-s', 'pucvmet' ]
-        self._names      = []
-        self._units      = []
-        self._process    = None
-
-        self._csv_output = csvfile or os.environ.get('ds_gpu_usage_csv', self.make_basename(prefix='ds-gpu-usage', extension='csv'))
-
-    def get_git_desc(self):
-        return subprocess.check_output(['git', 'describe', '--always', '--abbrev']).strip()
-
-    def make_basename(self, prefix, extension):
-        # Let us assume that this code is executed in the current git clone
-        return '%s.%s.%s.%s' % (prefix, self.get_git_desc(), int(time()), extension)
-
-    def stop(self):
-        if not self._process:
-            print("Trying to stop nvidia-smi but no more process, please fix.")
-            return
-
-        print("Ending nvidia-smi monitoring: PID", self._process.pid)
-        self._process.terminate()
-        print("Ended nvidia-smi monitoring ...")
-
-    def run(self):
-        print("Starting nvidia-smi monitoring")
-
-        # If the system has no CUDA setup, then this will fail.
-        try:
-            self._process = subprocess.Popen(self._cmd, stdout=subprocess.PIPE)
-        except OSError as ex:
-            print("Unable to start monitoring, check your environment:", ex)
-            return
-
-        writer = None
-        with open(self._csv_output, 'w') as f:
-            for line in iter(self._process.stdout.readline, ''):
-                d = self.ingest(line)
-
-                if line.startswith('# '):
-                    if len(self._names) == 0:
-                        self._names = d
-                        writer = csv.DictWriter(f, delimiter=str(','), quotechar=str('"'), fieldnames=d)
-                        writer.writeheader()
-                        continue
-                    if len(self._units) == 0:
-                        self._units = d
-                        continue
-                else:
-                    assert len(self._names) == len(self._units)
-                    assert len(d) == len(self._names)
-                    assert len(d) > 1
-                    writer.writerow(self.merge_line(d))
-                    f.flush()
-
-    def ingest(self, line):
-        return map(lambda x: x.replace('-', '0'), filter(lambda x: len(x) > 0, map(lambda x: x.strip(), line.split(' ')[1:])))
-
-    def merge_line(self, line):
-        return dict(zip(self._names, line))
-
-class GPUUsageChart():
-    def __init__(self, source, basename=None):
-        self._rows    = [ 'pwr', 'temp', 'sm', 'mem']
-        self._titles  = {
-            'pwr':  "Power (W)",
-            'temp': "Temperature (°C)",
-            'sm':   "Streaming Multiprocessors (%)",
-            'mem':  "Memory (%)"
-        }
-        self._data     = { }.fromkeys(self._rows)
-        self._csv      = source
-        self._basename = basename or os.environ.get('ds_gpu_usage_charts', 'gpu_usage_%%s_%d.png' % int(time.time()))
-
-        # This should make sure we start from anything clean.
-        plt.close("all")
-
-        try:
-            self.read()
-            for plot in self._rows:
-                self.produce_plot(plot)
-        except IOError as ex:
-            print("Unable to read", ex)
-
-    def append_data(self, row):
-        for bucket, value in row.iteritems():
-            if not bucket in self._rows:
-                continue
-
-            if not self._data[bucket]:
-                self._data[bucket] = {}
-
-            gpu = int(row['gpu'])
-            if not self._data[bucket].has_key(gpu):
-                self._data[bucket][gpu]  = [ value ]
-            else:
-                self._data[bucket][gpu] += [ value ]
-
-    def read(self):
-        print("Reading data from", self._csv)
-        with open(self._csv, 'r') as f:
-            for r in csv.DictReader(f):
-                self.append_data(r)
-
-    def produce_plot(self, key, with_spline=True):
-        png = self._basename % (key, )
-        print("Producing plot for", key, "as", png)
-        fig, axis = plt.subplots()
-        data = self._data[key]
-        if data is None:
-            print("Data was empty, aborting")
-            return
-
-        x = list(range(len(data[0])))
-        if with_spline:
-            x = map(lambda x: float(x), x)
-            x_sm = np.array(x)
-            x_smooth = np.linspace(x_sm.min(), x_sm.max(), 300)
-
-        for gpu, y in data.iteritems():
-            if with_spline:
-                y = map(lambda x: float(x), y)
-                y_sm = np.array(y)
-                y_smooth = spline(x, y, x_smooth, order=1)
-                axis.plot(x_smooth, y_smooth, label='GPU %d' % (gpu))
-            else:
-                axis.plot(x, y, label='GPU %d' % (gpu))
-
-        axis.legend(loc="upper right", frameon=False)
-        axis.set_xlabel("Time (s)")
-        axis.set_ylabel("%s" % self._titles[key])
-        fig.set_size_inches(24, 18)
-        plt.title("GPU Usage: %s" % self._titles[key])
-        plt.savefig(png, dpi=100)
-        plt.close(fig)