Shrutakeerti patch 2

ci_scripts/cppwin-tests.sh

@@ -2,19 +2,20 @@
 
 set -xe
 
-source $(dirname "$0")/all-vars.sh
-source $(dirname "$0")/all-utils.sh
-source $(dirname "$0")/asserts.sh
+source "$(dirname "$0")/all-vars.sh"
+source "$(dirname "$0")/all-utils.sh"
+source "$(dirname "$0")/asserts.sh"
 
 bitrate=$1
 set_ldc_sample_filename "${bitrate}"
 
 download_material "${CI_TMP_DIR}/ds"
 
-export PATH=${CI_TMP_DIR}/ds/:$PATH
+export PATH="${CI_TMP_DIR}/ds/:$PATH"
 
 check_versions
 
 ensure_cuda_usage "$2"
 
 run_basic_inference_tests
+

ci_scripts/cppwin_tflite-tests.sh

@@ -1,22 +1,21 @@
 #!/bin/bash
-
 set -xe
 
-source $(dirname "$0")/all-vars.sh
-source $(dirname "$0")/all-utils.sh
-source $(dirname "$0")/asserts.sh
+source "$(dirname "$0")/all-vars.sh"
+source "$(dirname "$0")/all-utils.sh"
+source "$(dirname "$0")/asserts.sh"
 
 bitrate=$1
 set_ldc_sample_filename "${bitrate}"
 
-model_source=${DEEPSPEECH_TEST_MODEL//.pb/.tflite}
+model_source="${DEEPSPEECH_TEST_MODEL//.pb/.tflite}"
 model_name=$(basename "${model_source}")
-model_name_mmap=$(basename "${model_source}")
+model_name_mmap="${model_name}.mmap"
 export DATA_TMP_DIR=${CI_TMP_DIR}
 
 download_material "${CI_TMP_DIR}/ds"
 
-export PATH=${CI_TMP_DIR}/ds/:$PATH
+export PATH="${CI_TMP_DIR}/ds/:$PATH"
 
 check_versions
 

ci_scripts/tf-package.sh

@@ -2,53 +2,41 @@
 
 set -xe
 
-source $(dirname $0)/tf-vars.sh
+source "$(dirname "$0")/tf-vars.sh"
 
-mkdir -p ${CI_ARTIFACTS_DIR} || true
+mkdir -p "${CI_ARTIFACTS_DIR}" || true
 
-cp ${DS_ROOT_TASK}/tensorflow/bazel_*.log ${CI_ARTIFACTS_DIR} || true
+cp "${DS_ROOT_TASK}/tensorflow/bazel_*.log" "${CI_ARTIFACTS_DIR}" || true
 
 OUTPUT_ROOT="${DS_ROOT_TASK}/tensorflow/bazel-bin"
 
-for output_bin in                                                            \
-    tensorflow/lite/experimental/c/libtensorflowlite_c.so                    \
-    tensorflow/tools/graph_transforms/transform_graph                        \
-    tensorflow/tools/graph_transforms/summarize_graph                        \
-    tensorflow/tools/benchmark/benchmark_model                               \
-    tensorflow/contrib/util/convert_graphdef_memmapped_format                \
+for output_bin in \
+    tensorflow/lite/experimental/c/libtensorflowlite_c.so \
+    tensorflow/tools/graph_transforms/transform_graph \
+    tensorflow/tools/graph_transforms/summarize_graph \
+    tensorflow/tools/benchmark/benchmark_model \
+    tensorflow/contrib/util/convert_graphdef_memmapped_format \
     tensorflow/lite/toco/toco;
 do
     if [ -f "${OUTPUT_ROOT}/${output_bin}" ]; then
-        cp ${OUTPUT_ROOT}/${output_bin} ${CI_ARTIFACTS_DIR}/
-    fi;
-done;
+        cp "${OUTPUT_ROOT}/${output_bin}" "${CI_ARTIFACTS_DIR}/"
+    fi
+done
 
 if [ -f "${OUTPUT_ROOT}/tensorflow/lite/tools/benchmark/benchmark_model" ]; then
-    cp ${OUTPUT_ROOT}/tensorflow/lite/tools/benchmark/benchmark_model ${CI_ARTIFACTS_DIR}/lite_benchmark_model
+    cp "${OUTPUT_ROOT}/tensorflow/lite/tools/benchmark/benchmark_model" "${CI_ARTIFACTS_DIR}/lite_benchmark_model"
 fi
 
-# It seems that bsdtar and gnutar are behaving a bit differently on the way
-# they deal with --exclude="./public/*" ; this caused ./DeepSpeech/tensorflow/core/public/
-# to be ditched when we just wanted to get rid of ./public/ on OSX.
-# Switching to gnutar (already needed for the --transform on DeepSpeech tasks)
-# does the trick.
 TAR_EXCLUDE="--exclude=./dls/*"
 if [ "${OS}" = "Darwin" ]; then
     TAR_EXCLUDE="--exclude=./dls/* --exclude=./public/* --exclude=./generic-worker/* --exclude=./homebrew/* --exclude=./homebrew.cache/* --exclude=./homebrew.logs/*"
-fi;
-
-# Make a tar of
-#  - /home/build-user/ (linux
-#  - /Users/build-user/TaskCluster/HeavyTasks/X/ (OSX)
-#  - C:\builds\tc-workdir\ (windows)
+fi
 
 if [ "${OS}" = "${CI_MSYS_VERSION}" ]; then
     export PATH=$PATH:'/c/Program Files/7-Zip/'
-    pushd ${DS_ROOT_TASK}
-        7z a '-xr!.\dls\' '-xr!.\tmp\' '-xr!.\msys64\' -snl -snh -so home.tar . | 7z a -si ${CI_ARTIFACTS_DIR}/home.tar.xz
-    popd
+    7z a '-xr!.\dls\' '-xr!.\tmp\' '-xr!.\msys64\' -snl -snh -so home.tar . | 7z a -si "${CI_ARTIFACTS_DIR}/home.tar.xz"
 else
-    ${TAR} -C ${DS_ROOT_TASK} ${TAR_EXCLUDE} -cf - . | ${XZ} > ${CI_ARTIFACTS_DIR}/home.tar.xz
+    tar -C "${DS_ROOT_TASK}" ${TAR_EXCLUDE} -cf - . | xz > "${CI_ARTIFACTS_DIR}/home.tar.xz"
 fi
 
 if [ "${OS}" = "Linux" ]; then
@@ -57,6 +45,7 @@ elif [ "${OS}" = "${CI_MSYS_VERSION}" ]; then
     SHA_SUM_GEN="sha256sum"
 elif [ "${OS}" = "Darwin" ]; then
     SHA_SUM_GEN="shasum -a 256"
-fi;
+fi
+
+${SHA_SUM_GEN} "${CI_ARTIFACTS_DIR}"/* > "${CI_ARTIFACTS_DIR}/checksums.txt"
 
-${SHA_SUM_GEN} ${CI_ARTIFACTS_DIR}/* > ${CI_ARTIFACTS_DIR}/checksums.txt

evaluate_tflite.py

@@ -1,4 +1,3 @@
-#!/usr/bin/env python
 # -*- coding: utf-8 -*-
 from __future__ import absolute_import, division, print_function
 
@@ -12,7 +11,6 @@
 
 from deepspeech import Model
 from deepspeech_training.util.evaluate_tools import calculate_and_print_report
-from deepspeech_training.util.flags import create_flags
 from functools import partial
 from multiprocessing import JoinableQueue, Process, cpu_count, Manager
 from six.moves import zip, range
@@ -52,7 +50,7 @@ def tflite_worker(model, scorer, queue_in, queue_out, gpu_mask):
         print(queue_out.qsize(), end='\r') # Update the current progress
         queue_in.task_done()
 
-def main(args, _):
+def main(args):
     manager = Manager()
     work_todo = JoinableQueue()   # this is where we are going to store input data
     work_done = manager.Queue()  # this where we are gonna push them out
@@ -80,7 +78,7 @@ def main(args, _):
             if not os.path.isabs(row['wav_filename']):
                 row['wav_filename'] = os.path.join(os.path.dirname(args.csv), row['wav_filename'])
             work_todo.put({'filename': row['wav_filename'], 'transcript': row['transcript']})
-            wav_filenames.extend(row['wav_filename'])
+            wav_filenames.append(row['wav_filename'])
 
     print('Totally %d wav entries found in csv\n' % count)
     work_todo.join()
@@ -122,5 +120,5 @@ def parse_args():
     return args
 
 if __name__ == '__main__':
-    create_flags()
-    absl.app.run(partial(main, parse_args()))
+    absl.app.run(main, parse_args())
+