Merge pull request #3050 from mozilla/update-r0.8

Update r0.8

Dockerfile

@@ -194,16 +194,17 @@ WORKDIR /DeepSpeech/
 RUN pip3 install tensorflow-gpu==1.15.0
 
 
-# Make DeepSpeech and install Python bindings
+# Build client.cc and install Python client and decoder bindings
 ENV TFDIR /tensorflow
 WORKDIR /DeepSpeech/native_client
 RUN make deepspeech
-WORKDIR /DeepSpeech/native_client/python
+
-RUN make bindings
+WORKDIR /DeepSpeech
-RUN pip3 install --upgrade dist/deepspeech*
+RUN cd native_client/python && make bindings
-WORKDIR /DeepSpeech/native_client/ctcdecode
+RUN pip3 install --upgrade native_client/python/dist/*.whl
-RUN make bindings
+
-RUN pip3 install --upgrade dist/*.whl
+RUN cd native_client/ctcdecode && make bindings
+RUN pip3 install --upgrade native_client/ctcdecode/dist/*.whl
 
 
 # << END Build and bind

GRAPH_VERSION

@@ -1 +0,0 @@
-6

GRAPH_VERSION

@@ -0,0 +1 @@
+training/deepspeech_training/GRAPH_VERSION

VERSION

@@ -1 +0,0 @@
-0.8.0-alpha.2

VERSION

@@ -0,0 +1 @@
+training/deepspeech_training/VERSION

bin/import_cv.py

@@ -127,7 +127,7 @@ def _maybe_convert_set(extracted_dir, source_csv, target_csv):
     pool.join()
 
     print('Writing "%s"...' % target_csv)
-    with open(target_csv, "w") as target_csv_file:
+    with open(target_csv, "w", encoding="utf-8", newline="") as target_csv_file:
         writer = csv.DictWriter(target_csv_file, fieldnames=FIELDNAMES)
         writer.writeheader()
         bar = progressbar.ProgressBar(max_value=len(rows), widgets=SIMPLE_BAR)

bin/import_cv2.py

@@ -127,7 +127,7 @@ def _maybe_convert_set(dataset, tsv_dir, audio_dir, filter_obj, space_after_ever
 
     output_csv = os.path.join(os.path.abspath(audio_dir), dataset + ".csv")
     print("Saving new DeepSpeech-formatted CSV file to: ", output_csv)
-    with open(output_csv, "w", encoding="utf-8") as output_csv_file:
+    with open(output_csv, "w", encoding="utf-8", newline="") as output_csv_file:
         print("Writing CSV file for DeepSpeech.py as: ", output_csv)
         writer = csv.DictWriter(output_csv_file, fieldnames=FIELDNAMES)
         writer.writeheader()

bin/import_lingua_libre.py

@@ -136,9 +136,9 @@ def _maybe_convert_sets(target_dir, extracted_data):
     pool.close()
     pool.join()
 
-    with open(target_csv_template.format("train"), "w") as train_csv_file:  # 80%
+    with open(target_csv_template.format("train"), "w", encoding="utf-8", newline="") as train_csv_file:  # 80%
-        with open(target_csv_template.format("dev"), "w") as dev_csv_file:  # 10%
+        with open(target_csv_template.format("dev"), "w", encoding="utf-8", newline="") as dev_csv_file:  # 10%
-            with open(target_csv_template.format("test"), "w") as test_csv_file:  # 10%
+            with open(target_csv_template.format("test"), "w", encoding="utf-8", newline="") as test_csv_file:  # 10%
                 train_writer = csv.DictWriter(train_csv_file, fieldnames=FIELDNAMES)
                 train_writer.writeheader()
                 dev_writer = csv.DictWriter(dev_csv_file, fieldnames=FIELDNAMES)

bin/import_m-ailabs.py

@@ -137,9 +137,9 @@ def _maybe_convert_sets(target_dir, extracted_data):
     pool.close()
     pool.join()
 
-    with open(target_csv_template.format("train"), "w") as train_csv_file:  # 80%
+    with open(target_csv_template.format("train"), "w", encoding="utf-8", newline="") as train_csv_file:  # 80%
-        with open(target_csv_template.format("dev"), "w") as dev_csv_file:  # 10%
+        with open(target_csv_template.format("dev"), "w", encoding="utf-8", newline="") as dev_csv_file:  # 10%
-            with open(target_csv_template.format("test"), "w") as test_csv_file:  # 10%
+            with open(target_csv_template.format("test"), "w", encoding="utf-8", newline="") as test_csv_file:  # 10%
                 train_writer = csv.DictWriter(train_csv_file, fieldnames=FIELDNAMES)
                 train_writer.writeheader()
                 dev_writer = csv.DictWriter(dev_csv_file, fieldnames=FIELDNAMES)

bin/import_slr57.py

@@ -159,9 +159,9 @@ def _maybe_convert_sets(target_dir, extracted_data):
     pool.close()
     pool.join()
 
-    with open(target_csv_template.format("train"), "w") as train_csv_file:  # 80%
+    with open(target_csv_template.format("train"), "w", encoding="utf-8", newline="") as train_csv_file:  # 80%
-        with open(target_csv_template.format("dev"), "w") as dev_csv_file:  # 10%
+        with open(target_csv_template.format("dev"), "w", encoding="utf-8", newline="") as dev_csv_file:  # 10%
-            with open(target_csv_template.format("test"), "w") as test_csv_file:  # 10%
+            with open(target_csv_template.format("test"), "w", encoding="utf-8", newline="") as test_csv_file:  # 10%
                 train_writer = csv.DictWriter(train_csv_file, fieldnames=FIELDNAMES)
                 train_writer.writeheader()
                 dev_writer = csv.DictWriter(dev_csv_file, fieldnames=FIELDNAMES)

bin/import_swc.py

@@ -461,7 +461,7 @@ def write_csvs(samples, language):
         base_dir = os.path.abspath(CLI_ARGS.base_dir)
         csv_path = os.path.join(base_dir, language + "-" + sub_set + ".csv")
         print('Writing "{}"...'.format(csv_path))
-        with open(csv_path, "w") as csv_file:
+        with open(csv_path, "w", encoding="utf-8", newline="") as csv_file:
             writer = csv.DictWriter(
                 csv_file, fieldnames=FIELDNAMES_EXT if CLI_ARGS.add_meta else FIELDNAMES
             )

bin/import_ts.py

@@ -131,9 +131,9 @@ def _maybe_convert_sets(target_dir, extracted_data, english_compatible=False):
     pool.close()
     pool.join()
 
-    with open(target_csv_template.format("train"), "w") as train_csv_file:  # 80%
+    with open(target_csv_template.format("train"), "w", encoding="utf-8", newline="") as train_csv_file:  # 80%
-        with open(target_csv_template.format("dev"), "w") as dev_csv_file:  # 10%
+        with open(target_csv_template.format("dev"), "w", encoding="utf-8", newline="") as dev_csv_file:  # 10%
-            with open(target_csv_template.format("test"), "w") as test_csv_file:  # 10%
+            with open(target_csv_template.format("test"), "w", encoding="utf-8", newline="") as test_csv_file:  # 10%
                 train_writer = csv.DictWriter(train_csv_file, fieldnames=FIELDNAMES)
                 train_writer.writeheader()
                 dev_writer = csv.DictWriter(dev_csv_file, fieldnames=FIELDNAMES)

bin/import_tuda.py

@@ -111,7 +111,7 @@ def write_csvs(extracted):
             CLI_ARGS.base_dir, "tuda-{}-{}.csv".format(TUDA_VERSION, sub_set)
         )
         print('Writing "{}"...'.format(csv_path))
-        with open(csv_path, "w") as csv_file:
+        with open(csv_path, "w", encoding="utf-8", newline="") as csv_file:
             writer = csv.DictWriter(csv_file, fieldnames=FIELDNAMES)
             writer.writeheader()
             set_dir = os.path.join(extracted, sub_set)

doc/Makefile

@@ -14,34 +14,23 @@ PIP_INSTALL   ?= pip3 install --user
 help:
 	@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
 
-.PHONY: help pip3 npm Makefile doxygen-c doxygen-java
+.PHONY: help pip3 Makefile
-
-doxygen-c:
-	cd ../ && doxygen doc/doxygen-c.conf
-
-doxygen-java:
-	cd ../ && doxygen doc/doxygen-java.conf
-
-doxygen-dotnet:
-	cd ../ && doxygen doc/doxygen-dotnet.conf
 
 pip3:
 	$(PIP_INSTALL) -r ../taskcluster/docs-requirements.txt
 
-npm:
-	npm install typedoc@0.17.4 typescript@3.8.3 @types/node@13.9.x
-
 submodule:
 	git submodule update --init --remote
 
 # Add submodule update dependency to Sphinx's "html" target
-html: Makefile submodule pip3 npm doxygen-c doxygen-java doxygen-dotnet
+html: Makefile submodule pip3
-	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
+	@PATH=$$HOME/.local/bin:`pwd`/../node_modules/.bin/:$$PATH \
+	     $(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
 
 dist: html
 	cd $(BUILDDIR)/html/ && zip -r9 ../../html.zip *
 
 # Catch-all target: route all unknown targets to Sphinx using the new
 # "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
-%: Makefile pip3 npm doxygen-c doxygen-java doxygen-dotnet
+%: Makefile pip3
 	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

doc/USING.rst

@@ -37,8 +37,8 @@ If you want to use the pre-trained English model for performing speech-to-text,
 
 .. code-block:: bash
 
-   wget https://github.com/mozilla/DeepSpeech/releases/download/v0.7.0/deepspeech-0.7.0-models.pbmm
+   wget https://github.com/mozilla/DeepSpeech/releases/download/v0.7.3/deepspeech-0.7.3-models.pbmm
-   wget https://github.com/mozilla/DeepSpeech/releases/download/v0.7.0/deepspeech-0.7.0-models.scorer
+   wget https://github.com/mozilla/DeepSpeech/releases/download/v0.7.3/deepspeech-0.7.3-models.scorer
 
 Model compatibility
 ^^^^^^^^^^^^^^^^^^^
@@ -113,7 +113,7 @@ Note: the following command assumes you `downloaded the pre-trained model <#gett
 
 .. code-block:: bash
 
-   deepspeech --model deepspeech-0.7.0-models.pbmm --scorer deepspeech-0.7.0-models.scorer --audio my_audio_file.wav
+   deepspeech --model deepspeech-0.7.3-models.pbmm --scorer deepspeech-0.7.3-models.scorer --audio my_audio_file.wav
 
 The ``--scorer`` argument is optional, and represents an external language model to be used when transcribing the audio.
 
@@ -177,7 +177,7 @@ Note: the following command assumes you `downloaded the pre-trained model <#gett
 
 .. code-block:: bash
 
-   ./deepspeech --model deepspeech-0.7.0-models.pbmm --scorer deepspeech-0.7.0-models.scorer --audio audio_input.wav
+   ./deepspeech --model deepspeech-0.7.3-models.pbmm --scorer deepspeech-0.7.3-models.scorer --audio audio_input.wav
 
 See the help output with ``./deepspeech -h`` for more details.
 

doc/conf.py

@@ -26,12 +26,14 @@ sys.path.insert(0, os.path.abspath('../'))
 
 autodoc_mock_imports = ['deepspeech']
 
-read_the_docs_build = os.environ.get('READTHEDOCS', None) == 'True'
+# This is in fact only relevant on ReadTheDocs, but we want to run the same way
-if read_the_docs_build:
+# on our CI as in RTD to avoid regressions on RTD that we would not catch on
+# TaskCluster
 import subprocess
-    subprocess.call('cd ../ && doxygen doc/doxygen-c.conf', shell=True)
+subprocess.check_call('cd ../ && npm install typedoc@0.17.4 typescript@3.8.3 @types/node@13.9.x', shell=True)
-    subprocess.call('cd ../ && doxygen doc/doxygen-java.conf', shell=True)
+subprocess.check_call('cd ../ && doxygen doc/doxygen-c.conf', shell=True)
-    subprocess.call('cd ../ && doxygen doc/doxygen-dotnet.conf', shell=True)
+subprocess.check_call('cd ../ && doxygen doc/doxygen-java.conf', shell=True)
+subprocess.check_call('cd ../ && doxygen doc/doxygen-dotnet.conf', shell=True)
 
 # -- General configuration ------------------------------------------------
 

doc/index.rst

@@ -20,15 +20,15 @@ To install and use DeepSpeech all you have to do is:
    pip3 install deepspeech
 
    # Download pre-trained English model files
-   curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.7.0/deepspeech-0.7.0-models.pbmm
+   curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.7.3/deepspeech-0.7.3-models.pbmm
-   curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.7.0/deepspeech-0.7.0-models.scorer
+   curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.7.3/deepspeech-0.7.3-models.scorer
 
    # Download example audio files
-   curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.7.0/audio-0.7.0.tar.gz
+   curl -LO https://github.com/mozilla/DeepSpeech/releases/download/v0.7.3/audio-0.7.3.tar.gz
-   tar xvf audio-0.7.0.tar.gz
+   tar xvf audio-0.7.3.tar.gz
 
    # Transcribe an audio file
-   deepspeech --model deepspeech-0.7.0-models.pbmm --scorer deepspeech-0.7.0-models.scorer --audio audio/2830-3980-0043.wav
+   deepspeech --model deepspeech-0.7.3-models.pbmm --scorer deepspeech-0.7.3-models.scorer --audio audio/2830-3980-0043.wav
 
 A pre-trained English model is available for use and can be downloaded following the instructions in :ref:`the usage docs <usage-docs>`. For the latest release, including pre-trained models and checkpoints, `see the GitHub releases page <https://github.com/mozilla/DeepSpeech/releases/latest>`_.
 
@@ -44,7 +44,7 @@ Quicker inference can be performed using a supported NVIDIA GPU on Linux. See th
    pip3 install deepspeech-gpu
 
    # Transcribe an audio file.
-   deepspeech --model deepspeech-0.7.0-models.pbmm --scorer deepspeech-0.7.0-models.scorer --audio audio/2830-3980-0043.wav
+   deepspeech --model deepspeech-0.7.3-models.pbmm --scorer deepspeech-0.7.3-models.scorer --audio audio/2830-3980-0043.wav
 
 Please ensure you have the required :ref:`CUDA dependencies <cuda-deps>`.
 

native_client/bazel_workspace_status_cmd.sh

@@ -22,8 +22,8 @@ echo "STABLE_TF_GIT_VERSION ${tf_git_rev}"
 pushd $(dirname "$0")
 ds_git_rev=$(git describe --long --tags)
 echo "STABLE_DS_GIT_VERSION ${ds_git_rev}"
-ds_version=$(cat ../VERSION)
+ds_version=$(cat ../training/deepspeech_training/VERSION)
 echo "STABLE_DS_VERSION ${ds_version}"
-ds_graph_version=$(cat ../GRAPH_VERSION)
+ds_graph_version=$(cat ../training/deepspeech_training/GRAPH_VERSION)
 echo "STABLE_DS_GRAPH_VERSION ${ds_graph_version}"
 popd

native_client/ctcdecode/setup.py

@@ -51,7 +51,7 @@ def maybe_rebuild(srcs, out_name, build_dir):
                      num_parallel=known_args.num_processes,
                      debug=debug)
 
-project_version = read('../../VERSION').strip()
+project_version = read('../../training/deepspeech_training/VERSION').strip()
 
 build_dir = 'temp_build/temp_build'
 

native_client/ctcdecode/swigwrapper.i

@@ -43,7 +43,13 @@ namespace std {
 %template(OutputVectorVector) std::vector<std::vector<Output>>;
 
 // Import only the error code enum definitions from deepspeech.h
-%ignore "";
+// We can't just do |%ignore "";| here because it affects this file globally (even
-%rename("%s", regexmatch$name="DS_ERR_") "";
+// files %include'd above). That causes SWIG to lose destructor information and
-%rename("%s", regexmatch$name="DeepSpeech_Error_Codes") "";
+// leads to leaks of the wrapper objects.
+// Instead we ignore functions and classes (structs), which are the only other
+// things in deepspeech.h. If we add some new construct to deepspeech.h we need
+// to update the ignore rules here to avoid exposing unwanted APIs in the decoder
+// package.
+%rename("$ignore", %$isfunction) "";
+%rename("$ignore", %$isclass) "";
 %include "../deepspeech.h"

native_client/javascript/Makefile

@@ -3,7 +3,7 @@ NODE_ABI_TARGET    ?=
 NODE_BUILD_VERBOSE ?= --verbose
 NPM_TOOL           ?= npm
 PROJECT_NAME       ?= deepspeech
-PROJECT_VERSION    ?= $(shell cat ../../VERSION | tr -d '\n')
+PROJECT_VERSION    ?= $(shell cat ../../training/deepspeech_training/VERSION | tr -d '\n')
 NPM_ROOT           ?= $(shell npm root)
 
 NODE_MODULES_BIN   ?= $(NPM_ROOT)/.bin/

native_client/python/setup.py

@@ -31,7 +31,7 @@ def main():
         sys.argv.remove('--project_name')
         sys.argv.pop(project_name_idx)
 
-    with open('../../VERSION', 'r') as ver:
+    with open('../../training/deepspeech_training/VERSION', 'r') as ver:
         project_version = ver.read().strip()
 
     class BuildExtFirst(build):

setup.py

@@ -7,20 +7,8 @@ from pkg_resources import parse_version
 from setuptools import find_packages, setup
 
 
-def get_decoder_pkg_url(version, artifacts_root=None):
+def get_tc_decoder_pkg_url(version, artifacts_root):
-    is_arm = 'arm' in platform.machine()
+    assert artifacts_root
-    is_mac = 'darwin' in sys.platform
-    is_win = 'win32' in sys.platform
-    is_64bit = sys.maxsize > (2**31 - 1)
-
-    if is_arm:
-        tc_arch = 'arm64-ctc' if is_64bit else 'arm-ctc'
-    elif is_mac:
-        tc_arch = 'osx-ctc'
-    elif is_win:
-        tc_arch = 'win-ctc'
-    else:
-        tc_arch = 'cpu-ctc'
 
     ds_version = parse_version(version)
     branch = "v{}".format(version)
@@ -37,20 +25,15 @@ def get_decoder_pkg_url(version, artifacts_root=None):
     if plat == 'windows':
         plat = 'win'
 
-    is_ucs2 = sys.maxunicode < 0x10ffff
-    m_or_mu = 'mu' if is_ucs2 else 'm'
-
     # ABI does not contain m / mu anymore after Python 3.8
     if sys.version_info.major == 3 and sys.version_info.minor >= 8:
         m_or_mu = ''
+    else:
+        is_ucs2 = sys.maxunicode < 0x10ffff
+        m_or_mu = 'mu' if is_ucs2 else 'm'
 
     pyver = ''.join(str(i) for i in sys.version_info[0:2])
 
-    if not artifacts_root:
-        artifacts_root = 'https://community-tc.services.mozilla.com/api/index/v1/task/project.deepspeech.deepspeech.native_client.{branch_name}.{tc_arch_string}/artifacts/public'.format(
-            branch_name=branch,
-            tc_arch_string=tc_arch)
-
     return 'ds_ctcdecoder @ {artifacts_root}/ds_ctcdecoder-{ds_version}-cp{pyver}-cp{pyver}{m_or_mu}-{platform}_{arch}.whl'.format(
         artifacts_root=artifacts_root,
         ds_version=ds_version,
@@ -66,8 +49,6 @@ def main():
     with open(str(version_file)) as fin:
         version = fin.read().strip()
 
-    decoder_pkg_url = get_decoder_pkg_url(version)
-
     install_requires_base = [
         'tensorflow == 1.15.2',
         'numpy',
@@ -89,18 +70,22 @@ def main():
         'soundfile',
     ]
 
+    decoder_pypi_dep = [
+        'ds_ctcdecoder == {}'.format(version)
+    ]
+
     # Due to pip craziness environment variables are the only consistent way to
     # get options into this script when doing `pip install`.
     tc_decoder_artifacts_root = os.environ.get('DECODER_ARTIFACTS_ROOT', '')
     if tc_decoder_artifacts_root:
         # We're running inside the TaskCluster environment, override the decoder
         # package URL with the one we just built.
-        decoder_pkg_url = get_decoder_pkg_url(version, tc_decoder_artifacts_root)
+        decoder_pkg_url = get_tc_decoder_pkg_url(version, tc_decoder_artifacts_root)
         install_requires = install_requires_base + [decoder_pkg_url]
     elif os.environ.get('DS_NODECODER', ''):
         install_requires = install_requires_base
     else:
-        install_requires = install_requires_base + [decoder_pkg_url]
+        install_requires = install_requires_base + decoder_pypi_dep
 
     setup(
         name='deepspeech_training',

taskcluster/docs-build.sh

@@ -5,6 +5,5 @@ set -xe
 THIS=$(dirname "$0")
 
 pushd ${THIS}/../
-  export PATH=$HOME/.local/bin:${THIS}/../doc/node_modules/.bin/:$PATH
   make -C doc/ dist
 popd

taskcluster/scriptworker-task-github.yml

@@ -49,7 +49,9 @@ build:
       - "node-package-tflite"
     cpp:
       - "darwin-amd64-cpu-opt"
+      - "darwin-amd64-tflite-opt"
       - "linux-amd64-cpu-opt"
+      - "linux-amd64-tflite-opt"
       - "linux-amd64-gpu-opt"
       - "linux-rpi3-cpu-opt"
       - "linux-arm64-cpu-opt"

taskcluster/scriptworker-task-pypi.yml

@@ -5,13 +5,16 @@ build:
     # - "linux-arm64-cpu-opt" Aarch64 packages are refused by upload.pypi.org
     - "darwin-amd64-cpu-opt"
     - "darwin-amd64-tflite-opt"
+    - "darwin-amd64-ctc-opt"
     - "linux-amd64-cpu-opt"
     - "linux-amd64-tflite-opt"
     - "linux-amd64-gpu-opt"
+    - "linux-amd64-ctc-opt"
     - "linux-rpi3-cpu-opt"
     - "win-amd64-cpu-opt"
     - "win-amd64-tflite-opt"
     - "win-amd64-gpu-opt"
+    - "win-amd64-ctc-opt"
   allowed:
     - "tag"
   ref_match: "refs/tags/"
@@ -24,13 +27,16 @@ build:
     python:
       - "darwin-amd64-cpu-opt"
       - "darwin-amd64-tflite-opt"
+      - "darwin-amd64-ctc-opt"
       - "linux-amd64-cpu-opt"
       - "linux-amd64-tflite-opt"
       - "linux-amd64-gpu-opt"
+      - "linux-amd64-ctc-opt"
       - "linux-rpi3-cpu-opt"
       - "win-amd64-cpu-opt"
       - "win-amd64-tflite-opt"
       - "win-amd64-gpu-opt"
+      - "win-amd64-ctc-opt"
       # - "linux-arm64-cpu-opt" Aarch64 packages are refused by upload.pypi.org
     nuget: []
   metadata:

taskcluster/tc-all-vars.sh

@@ -57,7 +57,7 @@ export DS_TFDIR=${DS_ROOT_TASK}/DeepSpeech/tf
 export DS_DSDIR=${DS_ROOT_TASK}/DeepSpeech/ds
 export DS_EXAMPLEDIR=${DS_ROOT_TASK}/DeepSpeech/examples
 
-export DS_VERSION="$(cat ${DS_DSDIR}/VERSION)"
+export DS_VERSION="$(cat ${DS_DSDIR}/training/deepspeech_training/VERSION)"
 
 export GRADLE_USER_HOME=${DS_ROOT_TASK}/gradle-cache
 export ANDROID_SDK_HOME=${DS_ROOT_TASK}/DeepSpeech/Android/SDK/

taskcluster/tc-train-tests.sh

@@ -8,6 +8,13 @@ extract_python_versions "$1" "pyver" "pyver_pkg" "py_unicode_type" "pyconf" "pya
 
 bitrate=$2
 
+decoder_src=$3
+
+if [ "$decoder_src" = "--pypi" ]; then
+    # Disable automatically picking up decoder package built in this CI group
+    export DECODER_ARTIFACTS_ROOT=""
+fi
+
 mkdir -p ${TASKCLUSTER_ARTIFACTS} || true
 mkdir -p /tmp/train || true
 mkdir -p /tmp/train_tflite || true

taskcluster/test-linux-opt-tag-base.tyml

@@ -0,0 +1,65 @@
+$if: '(event.event in build.allowed) && ((event.event != "tag") || (build.ref_match in event.head.ref))'
+then:
+  taskId: ${taskcluster.taskId}
+  provisionerId: ${taskcluster.docker.provisionerId}
+  workerType: ${taskcluster.docker.workerType}
+  taskGroupId: ${taskcluster.taskGroupId}
+  schedulerId: ${taskcluster.schedulerId}
+  dependencies:
+    $map: { $eval: build.dependencies }
+    each(b):
+      $eval: as_slugid(b)
+  created: { $fromNow: '0 sec' }
+  deadline: { $fromNow: '1 day' }
+  expires: { $fromNow: '7 days' }
+
+  extra:
+    github:
+      { $eval: taskcluster.github_events.pull_request }
+
+  payload:
+    maxRunTime: { $eval: to_int(build.maxRunTime) }
+    image: ${build.docker_image}
+
+    env:
+      $let:
+        training: { $eval: as_slugid(build.test_model_task) }
+        linux_amd64_build: { $eval: as_slugid("linux-amd64-cpu-opt") }
+        linux_amd64_tflite: { $eval: as_slugid("linux-amd64-tflite-opt") }
+        linux_amd64_ctc: { $eval: as_slugid("linux-amd64-ctc-opt") }
+      in:
+        DEEPSPEECH_ARTIFACTS_ROOT: https://community-tc.services.mozilla.com/api/queue/v1/task/${linux_amd64_build}/artifacts/public
+        DEEPSPEECH_ARTIFACTS_TFLITE_ROOT: https://community-tc.services.mozilla.com/api/queue/v1/task/${linux_amd64_tflite}/artifacts/public
+        DEEPSPEECH_TEST_MODEL: https://community-tc.services.mozilla.com/api/queue/v1/task/${training}/artifacts/public/output_graph.pb
+        DEEPSPEECH_PROD_MODEL: https://github.com/reuben/DeepSpeech/releases/download/v0.7.0-alpha.3/output_graph.pb
+        DEEPSPEECH_PROD_MODEL_MMAP: https://github.com/reuben/DeepSpeech/releases/download/v0.7.0-alpha.3/output_graph.pbmm
+        DECODER_ARTIFACTS_ROOT: https://community-tc.services.mozilla.com/api/queue/v1/task/${linux_amd64_ctc}/artifacts/public
+        PIP_DEFAULT_TIMEOUT: "60"
+        EXPECTED_TENSORFLOW_VERSION: "${build.tensorflow_git_desc}"
+
+    command:
+      - "/bin/bash"
+      - "--login"
+      - "-cxe"
+      - $let:
+          extraSystemSetup: { $eval: strip(str(build.system_setup)) }
+        in: >
+          ${aptEc2Mirrors} &&
+          apt-get -qq update && apt-get -qq -y install curl python-simplejson git pixz sox sudo wget && ${extraSystemSetup} &&
+          adduser --system --home ${system.homedir.linux} ${system.username} &&
+          cd ${system.homedir.linux} &&
+          echo -e "#!/bin/bash\nset -xe\n env && id && mkdir ~/DeepSpeech/ && git clone --quiet ${event.head.repo.url} ~/DeepSpeech/ds/ && cd ~/DeepSpeech/ds && git checkout --quiet ${event.head.sha}&& mkdir -p ${system.homedir.linux}/pyenv-root/ && wget -O - ${system.pyenv.linux.url} | tar -C ${system.homedir.linux}/pyenv-root/ -xzf -" > /tmp/clone.sh && chmod +x /tmp/clone.sh &&
+          sudo -H -u ${system.username} /bin/bash /tmp/clone.sh &&
+          sudo -H -u ${system.username} --preserve-env /bin/bash ${build.args.tests_cmdline}
+
+    artifacts:
+      "public":
+        type: "directory"
+        path: "/tmp/artifacts/"
+        expires: { $fromNow: '7 days' }
+
+  metadata:
+    name: ${build.metadata.name}
+    description: ${build.metadata.description}
+    owner: ${event.head.user.email}
+    source: ${event.head.repo.url}

taskcluster/test-training-pypi_16k-linux-amd64-py35m-opt.yml

@@ -0,0 +1,15 @@
+build:
+  template_file: test-linux-opt-tag-base.tyml
+  dependencies:
+    - "scriptworker-task-pypi"
+  allowed:
+    - "tag"
+  ref_match: "refs/tags/"
+  system_setup:
+    >
+      apt-get -qq update && apt-get -qq -y install ${training.packages_trusty.apt}
+  args:
+    tests_cmdline: "${system.homedir.linux}/DeepSpeech/ds/taskcluster/tc-train-tests.sh 3.5.8:m 16k --pypi"
+  metadata:
+    name: "DeepSpeech Linux AMD64 CPU 16kHz PyPI training Py3.5"
+    description: "Training a DeepSpeech LDC93S1 model for Linux/AMD64 16kHz Python 3.5, CPU only, optimized version, decoder package from PyPI"

taskcluster/test-training-pypi_16k-linux-amd64-py36m-opt.yml

@@ -0,0 +1,15 @@
+build:
+  template_file: test-linux-opt-tag-base.tyml
+  dependencies:
+    - "scriptworker-task-pypi"
+  allowed:
+    - "tag"
+  ref_match: "refs/tags/"
+  system_setup:
+    >
+      apt-get -qq update && apt-get -qq -y install ${training.packages_trusty.apt}
+  args:
+    tests_cmdline: "${system.homedir.linux}/DeepSpeech/ds/taskcluster/tc-train-tests.sh 3.6.10:m 16k --pypi"
+  metadata:
+    name: "DeepSpeech Linux AMD64 CPU 16kHz PyPI training Py3.6"
+    description: "Training a DeepSpeech LDC93S1 model for Linux/AMD64 16kHz Python 3.6, CPU only, optimized version, decoder package from PyPI"

taskcluster/test-training-pypi_16k-linux-amd64-py37m-opt.yml

@@ -0,0 +1,15 @@
+build:
+  template_file: test-linux-opt-tag-base.tyml
+  dependencies:
+    - "scriptworker-task-pypi"
+  allowed:
+    - "tag"
+  ref_match: "refs/tags/"
+  system_setup:
+    >
+      apt-get -qq update && apt-get -qq -y install ${training.packages_trusty.apt}
+  args:
+    tests_cmdline: "${system.homedir.linux}/DeepSpeech/ds/taskcluster/tc-train-tests.sh 3.7.6:m 16k --pypi"
+  metadata:
+    name: "DeepSpeech Linux AMD64 CPU 16kHz PyPI training Py3.7"
+    description: "Training a DeepSpeech LDC93S1 model for Linux/AMD64 16kHz Python 3.7, CPU only, optimized version, decoder package from PyPI"

taskcluster/test-training-pypi_8k-linux-amd64-py36m-opt.yml

@@ -0,0 +1,15 @@
+build:
+  template_file: test-linux-opt-tag-base.tyml
+  dependencies:
+    - "scriptworker-task-pypi"
+  allowed:
+    - "tag"
+  ref_match: "refs/tags/"
+  system_setup:
+    >
+      apt-get -qq update && apt-get -qq -y install ${training.packages_trusty.apt}
+  args:
+    tests_cmdline: "${system.homedir.linux}/DeepSpeech/ds/taskcluster/tc-train-tests.sh 3.6.10:m 8k --pypi"
+  metadata:
+    name: "DeepSpeech Linux AMD64 CPU 8kHz PyPI training Py3.6"
+    description: "Training a DeepSpeech LDC93S1 model for Linux/AMD64 8kHz Python 3.6, CPU only, optimized version, decoder package from PyPI"

taskcluster/test-training-pypi_8k-linux-amd64-py37m-opt.yml

@@ -0,0 +1,15 @@
+build:
+  template_file: test-linux-opt-tag-base.tyml
+  dependencies:
+    - "scriptworker-task-pypi"
+  allowed:
+    - "tag"
+  ref_match: "refs/tags/"
+  system_setup:
+    >
+      apt-get -qq update && apt-get -qq -y install ${training.packages_trusty.apt}
+  args:
+    tests_cmdline: "${system.homedir.linux}/DeepSpeech/ds/taskcluster/tc-train-tests.sh 3.7.6:m 8k  --pypi"
+  metadata:
+    name: "DeepSpeech Linux AMD64 CPU 8kHz PyPI training Py3.7"
+    description: "Training a DeepSpeech LDC93S1 model for Linux/AMD64 8kHz Python 3.7, CPU only, optimized version, decoder package from PyPI"

training/deepspeech_training/GRAPH_VERSION

@@ -1 +0,0 @@
-../../GRAPH_VERSION

training/deepspeech_training/GRAPH_VERSION

@@ -0,0 +1 @@
+6

training/deepspeech_training/VERSION

@@ -1 +0,0 @@
-../../VERSION

training/deepspeech_training/VERSION

@@ -0,0 +1 @@
+0.8.0-alpha.2

training/deepspeech_training/evaluate.py

@@ -61,7 +61,6 @@ def evaluate(test_csvs, create_model):
     # One rate per layer
     no_dropout = [None] * 6
     logits, _ = create_model(batch_x=batch_x,
-                             batch_size=FLAGS.test_batch_size,
                              seq_length=batch_x_len,
                              dropout=no_dropout)
 

training/deepspeech_training/util/feeding.py

@@ -151,7 +151,7 @@ def create_dataset(sources,
                               .map(process_fn, num_parallel_calls=tf.data.experimental.AUTOTUNE))
     if enable_cache:
         dataset = dataset.cache(cache_path)
-    dataset = (dataset.window(batch_size, drop_remainder=True).flat_map(batch_fn)
+    dataset = (dataset.window(batch_size, drop_remainder=train_phase).flat_map(batch_fn)
                       .prefetch(len(Config.available_devices)))
     return dataset
 
@@ -168,7 +168,7 @@ def split_audio_file(audio_path,
         segments = vad_split(frames, aggressiveness=aggressiveness)
         for segment in segments:
             segment_buffer, time_start, time_end = segment
-            samples = pcm_to_np(audio_format, segment_buffer)
+            samples = pcm_to_np(segment_buffer, audio_format)
             yield time_start, time_end, samples
 
     def to_mfccs(time_start, time_end, samples):