Remove full TF backend

.github/actions/host-build/action.yml

@@ -5,11 +5,8 @@ inputs:
     description: "Target arch for loading script (host/armv7/aarch64)"
     required: false
     default: "host"
-  flavor:
-    description: "Build flavor"
-    required: true
 runs:
   using: "composite"
   steps:
-    - run: ./ci_scripts/${{ inputs.arch }}-build.sh ${{ inputs.flavor }}
+    - run: ./ci_scripts/${{ inputs.arch }}-build.sh
       shell: bash

.github/actions/python-build/action.yml

@@ -1,9 +1,6 @@
 name: "Python binding"
 description: "Binding a python binding"
 inputs:
-  build_flavor:
-    description: "Python package name"
-    required: true
   numpy_build:
     description: "NumPy build dependecy"
     required: true
@@ -46,9 +43,6 @@ runs:
         set -xe
 
         PROJECT_NAME="stt"
-        if [ "${{ inputs.build_flavor }}" = "tflite" ]; then
-          PROJECT_NAME="stt-tflite"
-        fi
 
         OS=$(uname)
         if [ "${OS}" = "Linux" ]; then

.github/actions/run-tests/action.yml

@@ -4,9 +4,6 @@ inputs:
   runtime:
     description: "Runtime to use for running test"
     required: true
-  build-flavor:
-    description: "Running against TF or TFLite"
-    required: true
   model-kind:
     description: "Running against CI baked or production model"
     required: true
@@ -22,10 +19,7 @@ runs:
     - run: |
         set -xe
 
-        build=""
-        if [ "${{ inputs.build-flavor }}" = "tflite" ]; then
         build="_tflite"
-        fi
 
         model_kind=""
         if [ "${{ inputs.model-kind }}" = "prod" ]; then

ci_scripts/all-utils.sh

@@ -55,23 +55,6 @@ maybe_install_xldd()
   fi
 }
 
-# Checks whether we run a patched version of bazel.
-# Patching is required to dump computeKey() parameters to .ckd files
-# See bazel.patch
-# Return 0 (success exit code) on patched version, 1 on release version
-is_patched_bazel()
-{
-  bazel_version=$(bazel version | grep 'Build label:' | cut -d':' -f2)
-
-  bazel shutdown
-
-  if [ -z "${bazel_version}" ]; then
-    return 0;
-  else
-    return 1;
-  fi;
-}
-
 verify_bazel_rebuild()
 {
   bazel_explain_file="$1"

ci_scripts/build-utils.sh

@@ -9,21 +9,15 @@ do_bazel_build()
   cd ${DS_TFDIR}
   eval "export ${BAZEL_ENV_FLAGS}"
 
-  if [ "${_opt_or_dbg}" = "opt" ]; then
-    if is_patched_bazel; then
-      find ${DS_ROOT_TASK}/tensorflow/bazel-out/ -iname "*.ckd" | tar -cf ${DS_ROOT_TASK}/bazel-ckd-tf.tar -T -
-    fi;
-  fi;
-
   bazel ${BAZEL_OUTPUT_USER_ROOT} build \
-    -s --explain bazel_monolithic.log --verbose_explanations --experimental_strict_action_env --workspace_status_command="bash native_client/bazel_workspace_status_cmd.sh" --config=monolithic -c ${_opt_or_dbg} ${BAZEL_BUILD_FLAGS} ${BAZEL_TARGETS}
+    -s --explain bazel_explain.log --verbose_explanations \
+    --experimental_strict_action_env \
+    --workspace_status_command="bash native_client/bazel_workspace_status_cmd.sh" \
+    -c ${_opt_or_dbg} ${BAZEL_BUILD_FLAGS} ${BAZEL_TARGETS}
 
   if [ "${_opt_or_dbg}" = "opt" ]; then
-    if is_patched_bazel; then
+    verify_bazel_rebuild "${DS_ROOT_TASK}/tensorflow/bazel_explain.log"
-      find ${DS_ROOT_TASK}/tensorflow/bazel-out/ -iname "*.ckd" | tar -cf ${DS_ROOT_TASK}/bazel-ckd-ds.tar -T -
+  fi
-    fi;
-    verify_bazel_rebuild "${DS_ROOT_TASK}/tensorflow/bazel_monolithic.log"
-  fi;
 }
 
 shutdown_bazel()

ci_scripts/cpp-tests-prod.sh

@@ -1,26 +0,0 @@
-#!/bin/bash
-
-set -xe
-
-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=${STT_PROD_MODEL}
-model_name=$(basename "${model_source}")
-
-model_source_mmap=${STT_PROD_MODEL_MMAP}
-model_name_mmap=$(basename "${model_source_mmap}")
-
-download_model_prod
-
-download_material
-
-export PATH=${CI_TMP_DIR}/ds/:$PATH
-
-check_versions
-
-run_prod_inference_tests "${bitrate}"

ci_scripts/cpp-tests.sh

@@ -1,24 +0,0 @@
-#!/bin/bash
-
-set -xe
-
-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_data
-
-export PATH=${CI_TMP_DIR}/ds/:$PATH
-
-check_versions
-
-run_all_inference_tests
-
-run_multi_inference_tests
-
-run_cpp_only_inference_tests
-
-run_hotword_tests

ci_scripts/cppwin-tests.sh

@@ -1,20 +0,0 @@
-#!/bin/bash
-
-set -xe
-
-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
-
-check_versions
-
-ensure_cuda_usage "$2"
-
-run_basic_inference_tests

ci_scripts/electronjs-tests-prod.sh

@@ -1,48 +0,0 @@
-#!/bin/bash
-
-set -xe
-
-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=${STT_PROD_MODEL}
-model_name=$(basename "${model_source}")
-model_source_mmap=${STT_PROD_MODEL_MMAP}
-model_name_mmap=$(basename "${model_source_mmap}")
-
-download_model_prod
-
-download_data
-
-node --version
-npm --version
-
-symlink_electron
-
-export_node_bin_path
-
-which electron
-which node
-
-if [ "${OS}" = "Linux" ]; then
-  export DISPLAY=':99.0'
-  sudo Xvfb :99 -screen 0 1024x768x24 > /dev/null 2>&1 &
-  xvfb_process=$!
-fi
-
-node --version
-
-stt --version
-
-check_runtime_electronjs
-
-run_electronjs_prod_inference_tests "${bitrate}"
-
-if [ "${OS}" = "Linux" ]; then
-  sleep 1
-  sudo kill -9 ${xvfb_process} || true
-fi

ci_scripts/electronjs-tests.sh

@@ -1,41 +0,0 @@
-#!/bin/bash
-
-set -xe
-
-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_data
-
-node --version
-npm --version
-
-symlink_electron
-
-export_node_bin_path
-
-which electron
-which node
-
-if [ "${OS}" = "Linux" ]; then
-  export DISPLAY=':99.0'
-  sudo Xvfb :99 -screen 0 1024x768x24 > /dev/null 2>&1 &
-  xvfb_process=$!
-fi
-
-node --version
-
-stt --version
-
-check_runtime_electronjs
-
-run_electronjs_inference_tests
-
-if [ "${OS}" = "Linux" ]; then
-  sleep 1
-  sudo kill -9 ${xvfb_process} || true
-fi

ci_scripts/host-build.sh

@@ -2,8 +2,6 @@
 
 set -xe
 
-runtime=$1
-
 source $(dirname "$0")/all-vars.sh
 source $(dirname "$0")/all-utils.sh
 source $(dirname "$0")/build-utils.sh
@@ -15,10 +13,7 @@ BAZEL_TARGETS="
 //native_client:generate_scorer_package
 "
 
-if [ "${runtime}" = "tflite" ]; then
+BAZEL_BUILD_FLAGS="${BAZEL_OPT_FLAGS} ${BAZEL_EXTRA_FLAGS}"
-  BAZEL_BUILD_TFLITE="--define=runtime=tflite"
-fi;
-BAZEL_BUILD_FLAGS="${BAZEL_BUILD_TFLITE} ${BAZEL_OPT_FLAGS} ${BAZEL_EXTRA_FLAGS}"
 
 BAZEL_ENV_FLAGS="TF_NEED_CUDA=0"
 SYSTEM_TARGET=host

ci_scripts/node-tests-prod.sh

@@ -1,30 +0,0 @@
-#!/bin/bash
-
-set -xe
-
-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=${STT_PROD_MODEL}
-model_name=$(basename "${model_source}")
-model_source_mmap=${STT_PROD_MODEL_MMAP}
-model_name_mmap=$(basename "${model_source_mmap}")
-
-download_model_prod
-
-download_data
-
-node --version
-npm --version
-
-export_node_bin_path
-
-check_runtime_nodejs
-
-run_prod_inference_tests "${bitrate}"
-
-run_js_streaming_prod_inference_tests "${bitrate}"

ci_scripts/node-tests.sh

@@ -1,25 +0,0 @@
-#!/bin/bash
-
-set -xe
-
-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_data
-
-node --version
-npm --version
-
-export_node_bin_path
-
-check_runtime_nodejs
-
-run_all_inference_tests
-
-run_js_streaming_inference_tests
-
-run_hotword_tests

ci_scripts/package-utils.sh

@@ -30,10 +30,15 @@ package_native_client()
     win_lib="$win_lib -C ${tensorflow_dir}/bazel-bin/native_client/ libkenlm.so.if.lib"
   fi;
 
+  if [ -f "${tensorflow_dir}/bazel-bin/tensorflow/lite/libtensorflowlite.so.if.lib" ]; then
+    win_lib="$win_lib -C ${tensorflow_dir}/bazel-bin/tensorflow/lite/ libtensorflowlite.so.if.lib"
+  fi;
+
   ${TAR} --verbose -cf - \
     --transform='flags=r;s|README.coqui|KenLM_License_Info.txt|' \
     -C ${tensorflow_dir}/bazel-bin/native_client/ libstt.so \
     -C ${tensorflow_dir}/bazel-bin/native_client/ libkenlm.so \
+    -C ${tensorflow_dir}/bazel-bin/tensorflow/lite/ libtensorflowlite.so \
     ${win_lib} \
     -C ${tensorflow_dir}/bazel-bin/native_client/ generate_scorer_package \
     -C ${stt_dir}/ LICENSE \
@@ -94,5 +99,8 @@ package_libstt_as_zip()
     echo "Please specify artifact name."
   fi;
 
-  ${ZIP} -r9 --junk-paths "${artifacts_dir}/${artifact_name}" ${tensorflow_dir}/bazel-bin/native_client/libstt.so
+  ${ZIP} -r9 --junk-paths "${artifacts_dir}/${artifact_name}" \
+    ${tensorflow_dir}/bazel-bin/native_client/libstt.so \
+    ${tensorflow_dir}/bazel-bin/native_client/libkenlm.so \
+    ${tensorflow_dir}/bazel-bin/tensorflow/lite/libtensorflowlite.so
 }

ci_scripts/python-tests-prod.sh

@@ -1,29 +0,0 @@
-#!/bin/bash
-
-set -xe
-
-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=${STT_PROD_MODEL}
-model_name=$(basename "${model_source}")
-
-model_source_mmap=${STT_PROD_MODEL_MMAP}
-model_name_mmap=$(basename "${model_source_mmap}")
-
-download_model_prod
-
-download_material
-
-export_py_bin_path
-
-which stt
-stt --version
-
-run_prod_inference_tests "${bitrate}"
-
-run_prod_concurrent_stream_tests "${bitrate}"

ci_scripts/python-tests.sh

@@ -1,21 +0,0 @@
-#!/bin/bash
-
-set -xe
-
-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_data
-
-export_py_bin_path
-
-which stt
-stt --version
-
-run_all_inference_tests
-
-run_hotword_tests

ci_scripts/tf-build.sh

@@ -6,7 +6,7 @@ set -o pipefail
 source $(dirname $0)/tf-vars.sh
 
 pushd ${DS_ROOT_TASK}/tensorflow/
-    BAZEL_BUILD="bazel ${BAZEL_OUTPUT_USER_ROOT} build -s --explain bazel_monolithic_tf.log --verbose_explanations --experimental_strict_action_env --config=monolithic"
+    BAZEL_BUILD="bazel ${BAZEL_OUTPUT_USER_ROOT} build -s"
 
     # Start a bazel process to ensure reliability on Windows and avoid:
     # FATAL: corrupt installation: file 'c:\builds\tc-workdir\.bazel_cache/install/6b1660721930e9d5f231f7d2a626209b/_embedded_binaries/build-runfiles.exe' missing.
@@ -23,13 +23,10 @@ pushd ${DS_ROOT_TASK}/tensorflow/
 
     case "$1" in
     "--windows-cpu")
-        echo "" | TF_NEED_CUDA=0 ./configure && ${BAZEL_BUILD} ${OPT_OR_DBG} ${BAZEL_OPT_FLAGS} ${BAZEL_EXTRA_FLAGS} ${BUILD_TARGET_LIBSTT} ${BUILD_TARGET_LITE_LIB} --workspace_status_command="bash native_client/bazel_workspace_status_cmd.sh"
+        echo "" | TF_NEED_CUDA=0 ./configure && ${BAZEL_BUILD} ${OPT_OR_DBG} ${BAZEL_OPT_FLAGS} ${BAZEL_EXTRA_FLAGS} ${BUILD_TARGET_LITE_LIB}
         ;;
     "--linux-cpu"|"--darwin-cpu")
-        echo "" | TF_NEED_CUDA=0 ./configure && ${BAZEL_BUILD} ${OPT_OR_DBG} ${BAZEL_OPT_FLAGS} ${BAZEL_EXTRA_FLAGS} ${BUILD_TARGET_LIB_CPP_API} ${BUILD_TARGET_LITE_LIB}
+        echo "" | TF_NEED_CUDA=0 ./configure && ${BAZEL_BUILD} ${OPT_OR_DBG} ${BAZEL_OPT_FLAGS} ${BAZEL_EXTRA_FLAGS} ${BUILD_TARGET_LITE_LIB}
-        ;;
-    "--linux-cuda"|"--windows-cuda")
-        eval "export ${TF_CUDA_FLAGS}" && (echo "" | TF_NEED_CUDA=1 ./configure) && ${BAZEL_BUILD} ${OPT_OR_DBG} ${BAZEL_CUDA_FLAGS} ${BAZEL_EXTRA_FLAGS} ${BAZEL_OPT_FLAGS} ${BUILD_TARGET_LIB_CPP_API}
         ;;
     "--linux-armv7")
         echo "" | TF_NEED_CUDA=0 ./configure && ${BAZEL_BUILD} ${OPT_OR_DBG} ${BAZEL_ARM_FLAGS} ${BAZEL_EXTRA_FLAGS} ${BUILD_TARGET_LITE_LIB}

ci_scripts/tf-package.sh

@@ -6,26 +6,17 @@ source $(dirname $0)/tf-vars.sh
 
 mkdir -p ${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/lite/libtensorflow.so        \
-    tensorflow/tools/graph_transforms/transform_graph                        \
+    tensorflow/lite/libtensorflow.so.if.lib \
-    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} ${CI_ARTIFACTS_DIR}/
     fi;
-done;
+done
-
-if [ -f "${OUTPUT_ROOT}/tensorflow/lite/tools/benchmark/benchmark_model" ]; then
-    cp ${OUTPUT_ROOT}/tensorflow/lite/tools/benchmark/benchmark_model ${CI_ARTIFACTS_DIR}/lite_benchmark_model
-fi
 
 # It seems that bsdtar and gnutar are behaving a bit differently on the way
 # they deal with --exclude="./public/*" ; this caused ./STT/tensorflow/core/public/

ci_scripts/tf-setup.sh

@@ -5,12 +5,7 @@ set -ex
 source $(dirname $0)/tf-vars.sh
 
 install_android=
-install_cuda=
 case "$1" in
-    "--linux-cuda"|"--windows-cuda")
-    install_cuda=yes
-    ;;
-
     "--android-armv7"|"--android-arm64")
     install_android=yes
     ;;
@@ -29,11 +24,6 @@ download()
 mkdir -p ${DS_ROOT_TASK}/dls || true
 download $BAZEL_URL $BAZEL_SHA256
 
-if [ ! -z "${install_cuda}" ]; then
-    download $CUDA_URL $CUDA_SHA256
-    download $CUDNN_URL $CUDNN_SHA256
-fi;
-
 if [ ! -z "${install_android}" ]; then
     download $ANDROID_NDK_URL $ANDROID_NDK_SHA256
     download $ANDROID_SDK_URL $ANDROID_SDK_SHA256
@@ -63,30 +53,6 @@ bazel version
 
 bazel shutdown
 
-if [ ! -z "${install_cuda}" ]; then
-    # Install CUDA and CuDNN
-    mkdir -p ${DS_ROOT_TASK}/STT/CUDA/ || true
-    pushd ${DS_ROOT_TASK}
-        CUDA_FILE=`basename ${CUDA_URL}`
-        PERL5LIB=. sh ${DS_ROOT_TASK}/dls/${CUDA_FILE} --silent --override --toolkit --toolkitpath=${DS_ROOT_TASK}/STT/CUDA/ --defaultroot=${DS_ROOT_TASK}/STT/CUDA/
-
-        CUDNN_FILE=`basename ${CUDNN_URL}`
-        tar xvf ${DS_ROOT_TASK}/dls/${CUDNN_FILE} --strip-components=1 -C ${DS_ROOT_TASK}/STT/CUDA/
-    popd
-
-    LD_LIBRARY_PATH=${DS_ROOT_TASK}/STT/CUDA/lib64/:${DS_ROOT_TASK}/STT/CUDA/lib64/stubs/:$LD_LIBRARY_PATH
-    export LD_LIBRARY_PATH
-
-    # We might lack libcuda.so.1 symlink, let's fix as upstream does:
-    # https://github.com/tensorflow/tensorflow/pull/13811/files?diff=split#diff-2352449eb75e66016e97a591d3f0f43dR96
-    if [ ! -h "${DS_ROOT_TASK}/STT/CUDA/lib64/stubs/libcuda.so.1" ]; then
-        ln -s "${DS_ROOT_TASK}/STT/CUDA/lib64/stubs/libcuda.so" "${DS_ROOT_TASK}/STT/CUDA/lib64/stubs/libcuda.so.1"
-    fi;
-
-else
-    echo "No CUDA/CuDNN to install"
-fi
-
 if [ ! -z "${install_android}" ]; then
     mkdir -p ${DS_ROOT_TASK}/STT/Android/SDK || true
     ANDROID_NDK_FILE=`basename ${ANDROID_NDK_URL}`

ci_scripts/tf-vars.sh

@@ -9,13 +9,6 @@ if [ "${OS}" = "Linux" ]; then
     BAZEL_URL=https://github.com/bazelbuild/bazel/releases/download/3.1.0/bazel-3.1.0-installer-linux-x86_64.sh
     BAZEL_SHA256=7ba815cbac712d061fe728fef958651512ff394b2708e89f79586ec93d1185ed
 
-    CUDA_URL=http://developer.download.nvidia.com/compute/cuda/10.1/Prod/local_installers/cuda_10.1.243_418.87.00_linux.run
-    CUDA_SHA256=e7c22dc21278eb1b82f34a60ad7640b41ad3943d929bebda3008b72536855d31
-
-    # From https://gitlab.com/nvidia/cuda/blob/centos7/10.1/devel/cudnn7/Dockerfile
-    CUDNN_URL=http://developer.download.nvidia.com/compute/redist/cudnn/v7.6.0/cudnn-10.1-linux-x64-v7.6.0.64.tgz
-    CUDNN_SHA256=e956c6f9222fcb867a10449cfc76dee5cfd7c7531021d95fe9586d7e043b57d7
-
     ANDROID_NDK_URL=https://dl.google.com/android/repository/android-ndk-r18b-linux-x86_64.zip
     ANDROID_NDK_SHA256=4f61cbe4bbf6406aa5ef2ae871def78010eed6271af72de83f8bd0b07a9fd3fd
 
@@ -48,8 +41,6 @@ elif [ "${OS}" = "${CI_MSYS_VERSION}" ]; then
     BAZEL_URL=https://github.com/bazelbuild/bazel/releases/download/3.1.0/bazel-3.1.0-windows-x86_64.exe
     BAZEL_SHA256=776db1f4986dacc3eda143932f00f7529f9ee65c7c1c004414c44aaa6419d0e9
 
-    CUDA_INSTALL_DIRECTORY=$(cygpath 'C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v10.1')
-
     TAR=/usr/bin/tar.exe
 elif [ "${OS}" = "Darwin" ]; then
     if [ -z "${CI_TASK_DIR}" -o -z "${CI_ARTIFACTS_DIR}" ]; then
@@ -89,7 +80,6 @@ fi;
 export PATH
 
 if [ "${OS}" = "Linux" ]; then
-    export LD_LIBRARY_PATH=${DS_ROOT_TASK}/STT/CUDA/lib64/:${DS_ROOT_TASK}/STT/CUDA/lib64/stubs/:$LD_LIBRARY_PATH
     export ANDROID_SDK_HOME=${DS_ROOT_TASK}/STT/Android/SDK/
     export ANDROID_NDK_HOME=${DS_ROOT_TASK}/STT/Android/android-ndk-r18b/
 fi;
@@ -160,27 +150,15 @@ export BAZEL_OUTPUT_USER_ROOT
 
 NVCC_COMPUTE="3.5"
 
-### Define build parameters/env variables that we will re-ues in sourcing scripts.
-if [ "${OS}" = "${CI_MSYS_VERSION}" ]; then
-    TF_CUDA_FLAGS="TF_CUDA_CLANG=0 TF_CUDA_VERSION=10.1 TF_CUDNN_VERSION=7.6.0 CUDNN_INSTALL_PATH=\"${CUDA_INSTALL_DIRECTORY}\" TF_CUDA_PATHS=\"${CUDA_INSTALL_DIRECTORY}\" TF_CUDA_COMPUTE_CAPABILITIES=\"${NVCC_COMPUTE}\""
-else
-    TF_CUDA_FLAGS="TF_CUDA_CLANG=0 TF_CUDA_VERSION=10.1 TF_CUDNN_VERSION=7.6.0 CUDNN_INSTALL_PATH=\"${DS_ROOT_TASK}/STT/CUDA\" TF_CUDA_PATHS=\"${DS_ROOT_TASK}/STT/CUDA\" TF_CUDA_COMPUTE_CAPABILITIES=\"${NVCC_COMPUTE}\""
-fi
 BAZEL_ARM_FLAGS="--config=rpi3 --config=rpi3_opt --copt=-DTFLITE_WITH_RUY_GEMV"
 BAZEL_ARM64_FLAGS="--config=rpi3-armv8 --config=rpi3-armv8_opt --copt=-DTFLITE_WITH_RUY_GEMV"
 BAZEL_ANDROID_ARM_FLAGS="--config=android --config=android_arm --action_env ANDROID_NDK_API_LEVEL=21 --cxxopt=-std=c++14 --copt=-D_GLIBCXX_USE_C99 --copt=-DTFLITE_WITH_RUY_GEMV"
 BAZEL_ANDROID_ARM64_FLAGS="--config=android --config=android_arm64 --action_env ANDROID_NDK_API_LEVEL=21 --cxxopt=-std=c++14 --copt=-D_GLIBCXX_USE_C99 --copt=-DTFLITE_WITH_RUY_GEMV"
-BAZEL_CUDA_FLAGS="--config=cuda"
-if [ "${OS}" = "Linux" ]; then
-    # constexpr usage in tensorflow's absl dep fails badly because of gcc-5
-    # so let's skip that
-    BAZEL_CUDA_FLAGS="${BAZEL_CUDA_FLAGS} --copt=-DNO_CONSTEXPR_FOR_YOU=1"
-fi
 BAZEL_IOS_ARM64_FLAGS="--config=ios_arm64 --define=runtime=tflite --copt=-DTFLITE_WITH_RUY_GEMV"
 BAZEL_IOS_X86_64_FLAGS="--config=ios_x86_64 --define=runtime=tflite --copt=-DTFLITE_WITH_RUY_GEMV"
 
 if [ "${OS}" != "${CI_MSYS_VERSION}" ]; then
-    BAZEL_EXTRA_FLAGS="--config=noaws --config=nogcp --config=nohdfs --config=nonccl --copt=-fvisibility=hidden"
+    BAZEL_EXTRA_FLAGS="--config=noaws --config=nogcp --config=nohdfs --config=nonccl"
 fi
 
 if [ "${OS}" = "Darwin" ]; then
@@ -189,11 +167,5 @@ fi
 
 ### Define build targets that we will re-ues in sourcing scripts.
 BUILD_TARGET_LIB_CPP_API="//tensorflow:tensorflow_cc"
-BUILD_TARGET_GRAPH_TRANSFORMS="//tensorflow/tools/graph_transforms:transform_graph"
+BUILD_TARGET_LITE_LIB="//tensorflow/lite:libtensorflowlite.so"
-BUILD_TARGET_GRAPH_SUMMARIZE="//tensorflow/tools/graph_transforms:summarize_graph"
-BUILD_TARGET_GRAPH_BENCHMARK="//tensorflow/tools/benchmark:benchmark_model"
-#BUILD_TARGET_CONVERT_MMAP="//tensorflow/contrib/util:convert_graphdef_memmapped_format"
-BUILD_TARGET_TOCO="//tensorflow/lite/toco:toco"
-BUILD_TARGET_LITE_BENCHMARK="//tensorflow/lite/tools/benchmark:benchmark_model"
-BUILD_TARGET_LITE_LIB="//tensorflow/lite/c:libtensorflowlite_c.so"
 BUILD_TARGET_LIBSTT="//native_client:libstt.so"

native_client/BUILD

@@ -1,22 +1,9 @@
 # Description: Coqui STT native client library.
 
-load("@org_tensorflow//tensorflow:tensorflow.bzl", "tf_cc_shared_object", "tf_copts", "lrt_if_needed")
+load("@org_tensorflow//tensorflow:tensorflow.bzl", "lrt_if_needed")
-load("@local_config_cuda//cuda:build_defs.bzl", "if_cuda")
 load("@com_github_nelhage_rules_boost//:boost/boost.bzl", "boost_deps")
 load("@build_bazel_rules_apple//apple:ios.bzl", "ios_static_framework")
 
-load(
-    "@org_tensorflow//tensorflow/lite:build_def.bzl",
-    "tflite_copts",
-    "tflite_linkopts",
-)
-
-config_setting(
-    name = "tflite",
-    define_values = {
-        "runtime": "tflite",
-    },
-)
 
 config_setting(
     name = "rpi3",
@@ -85,7 +72,7 @@ LINUX_LINKOPTS = [
     "-Wl,-export-dynamic",
 ]
 
-tf_cc_shared_object(
+cc_binary(
     name = "libkenlm.so",
     srcs = glob([
         "kenlm/lm/*.hh",
@@ -107,8 +94,19 @@ tf_cc_shared_object(
     }),
     defines = ["KENLM_MAX_ORDER=6"],
     includes = ["kenlm"],
-    framework_so = [],
+    linkshared = 1,
-    linkopts = [],
+    linkopts = select({
+        "//tensorflow:ios": [
+            "-Wl,-install_name,@rpath/libkenlm.so",
+        ],
+        "//tensorflow:macos": [
+            "-Wl,-install_name,@rpath/libkenlm.so",
+        ],
+        "//tensorflow:windows": [],
+        "//conditions:default": [
+            "-Wl,-soname,libkenlm.so",
+        ],
+    }),
 )
 
 cc_library(
@@ -132,6 +130,20 @@ cc_library(
     copts = ["-fexceptions"],
 )
 
+cc_library(
+    name="tflite",
+    hdrs = [
+        "//tensorflow/lite:model.h",
+        "//tensorflow/lite/kernels:register.h",
+        "//tensorflow/lite/tools/evaluation:utils.h",
+    ],
+    srcs = [
+        "//tensorflow/lite:libtensorflowlite.so",
+    ],
+    includes = ["tensorflow"],
+    deps = ["//tensorflow/lite:libtensorflowlite.so"],
+)
+
 cc_library(
     name = "coqui_stt_bundle",
     srcs = [
@@ -142,17 +154,10 @@ cc_library(
         "modelstate.h",
         "workspace_status.cc",
         "workspace_status.h",
-    ] + select({
-        "//native_client:tflite": [
         "tflitemodelstate.h",
         "tflitemodelstate.cc",
-        ],
+    ] + DECODER_SOURCES,
-        "//conditions:default": [
+    copts = select({
-            "tfmodelstate.h",
-            "tfmodelstate.cc",
-        ],
-    }) + DECODER_SOURCES,
-    copts = tf_copts(allow_exceptions=True) + select({
         # -fvisibility=hidden is not required on Windows, MSCV hides all declarations by default
         "//tensorflow:windows": ["/w"],
         # -Wno-sign-compare to silent a lot of warnings from tensorflow itself,
@@ -161,9 +166,6 @@ cc_library(
             "-Wno-sign-compare",
             "-fvisibility=hidden",
         ],
-    }) + select({
-        "//native_client:tflite": ["-DUSE_TFLITE"],
-        "//conditions:default": ["-UUSE_TFLITE"],
     }),
     linkopts = lrt_if_needed() + select({
         "//tensorflow:macos": [],
@@ -174,64 +176,32 @@ cc_library(
         # Bazel is has too strong opinions about static linking, so it's
         # near impossible to get it to link a DLL against another DLL on Windows.
         # We simply force the linker option manually here as a hacky fix.
-        "//tensorflow:windows": ["bazel-out/x64_windows-opt/bin/native_client/libkenlm.so.if.lib"],
+        "//tensorflow:windows": [
+            "bazel-out/x64_windows-opt/bin/native_client/libkenlm.so.if.lib",
+            "bazel-out/x64_windows-opt/bin/tensorflow/lite/libtensorflowlite.so.if.lib",
+        ],
         "//conditions:default": [],
-    }) + tflite_linkopts() + DECODER_LINKOPTS,
+    }) + DECODER_LINKOPTS,
     includes = DECODER_INCLUDES,
-    deps = select({
+    deps = [":kenlm", ":tflite"],
-        "//native_client:tflite": [
-            "//tensorflow/lite/kernels:builtin_ops",
-            "//tensorflow/lite/tools/evaluation:utils",
-        ],
-        "//conditions:default": [
-            "//tensorflow/core:core_cpu",
-            "//tensorflow/core:direct_session",
-            "//third_party/eigen3",
-            #"//tensorflow/core:all_kernels",
-            ### => Trying to be more fine-grained
-            ### Use bin/ops_in_graph.py to list all the ops used by a frozen graph.
-            ### CPU only build, libstt.so file size reduced by ~50%
-            "//tensorflow/core/kernels:spectrogram_op",  # AudioSpectrogram
-            "//tensorflow/core/kernels:bias_op",  # BiasAdd
-            "//tensorflow/core/kernels:cast_op",  # Cast
-            "//tensorflow/core/kernels:concat_op",  # ConcatV2
-            "//tensorflow/core/kernels:constant_op",  # Const, Placeholder
-            "//tensorflow/core/kernels:shape_ops",  # ExpandDims, Shape
-            "//tensorflow/core/kernels:gather_nd_op",  # GatherNd
-            "//tensorflow/core/kernels:identity_op",  # Identity
-            "//tensorflow/core/kernels:immutable_constant_op",  # ImmutableConst (used in memmapped models)
-            "//tensorflow/core/kernels:deepspeech_cwise_ops",  # Less, Minimum, Mul
-            "//tensorflow/core/kernels:matmul_op",  # MatMul
-            "//tensorflow/core/kernels:reduction_ops",  # Max
-            "//tensorflow/core/kernels:mfcc_op",  # Mfcc
-            "//tensorflow/core/kernels:no_op",  # NoOp
-            "//tensorflow/core/kernels:pack_op",  # Pack
-            "//tensorflow/core/kernels:sequence_ops",  # Range
-            "//tensorflow/core/kernels:relu_op",  # Relu
-            "//tensorflow/core/kernels:reshape_op",  # Reshape
-            "//tensorflow/core/kernels:softmax_op",  # Softmax
-            "//tensorflow/core/kernels:tile_ops",  # Tile
-            "//tensorflow/core/kernels:transpose_op",  # Transpose
-            "//tensorflow/core/kernels:rnn_ops",  # BlockLSTM
-            # And we also need the op libs for these ops used in the model:
-            "//tensorflow/core:audio_ops_op_lib",  # AudioSpectrogram, Mfcc
-            "//tensorflow/core:rnn_ops_op_lib",  # BlockLSTM
-            "//tensorflow/core:math_ops_op_lib",  # Cast, Less, Max, MatMul, Minimum, Range
-            "//tensorflow/core:array_ops_op_lib",  # ConcatV2, Const, ExpandDims, Fill, GatherNd, Identity, Pack, Placeholder, Reshape, Tile, Transpose
-            "//tensorflow/core:no_op_op_lib",  # NoOp
-            "//tensorflow/core:nn_ops_op_lib",  # Relu, Softmax, BiasAdd
-            # And op libs for these ops brought in by dependencies of dependencies to silence unknown OpKernel warnings:
-            "//tensorflow/core:dataset_ops_op_lib",  # UnwrapDatasetVariant, WrapDatasetVariant
-            "//tensorflow/core:sendrecv_ops_op_lib",  # _HostRecv, _HostSend, _Recv, _Send
-        ],
-    }) + if_cuda([
-        "//tensorflow/core:core",
-    ]) + [":kenlm"],
 )
 
-tf_cc_shared_object(
+cc_binary(
     name = "libstt.so",
     deps = [":coqui_stt_bundle"],
+    linkshared = 1,
+    linkopts = select({
+        "//tensorflow:ios": [
+            "-Wl,-install_name,@rpath/libstt.so",
+        ],
+        "//tensorflow:macos": [
+            "-Wl,-install_name,@rpath/libstt.so",
+        ],
+        "//tensorflow:windows": [],
+        "//conditions:default": [
+            "-Wl,-soname,libstt.so",
+        ],
+    }),
 )
 
 ios_static_framework(

native_client/definitions.mk

@@ -20,8 +20,8 @@ endif
 
 STT_BIN       := stt$(PLATFORM_EXE_SUFFIX)
 CFLAGS_STT    := -std=c++11 -o $(STT_BIN)
-LINK_STT      := -lstt -lkenlm
+LINK_STT      := -lstt -lkenlm -ltensorflowlite
-LINK_PATH_STT := -L${TFDIR}/bazel-bin/native_client
+LINK_PATH_STT := -L${TFDIR}/bazel-bin/native_client -L${TFDIR}/bazel-bin/tensorflow/lite
 
 ifeq ($(TARGET),host)
 TOOLCHAIN       :=
@@ -61,7 +61,7 @@ TOOL_CC     := cl.exe
 TOOL_CXX    := cl.exe
 TOOL_LD     := link.exe
 TOOL_LIBEXE := lib.exe
-LINK_STT      := $(shell cygpath "$(TFDIR)/bazel-bin/native_client/libstt.so.if.lib") $(shell cygpath "$(TFDIR)/bazel-bin/native_client/libkenlm.so.if.lib")
+LINK_STT      := $(shell cygpath "$(TFDIR)/bazel-bin/native_client/libstt.so.if.lib") $(shell cygpath "$(TFDIR)/bazel-bin/native_client/libkenlm.so.if.lib") $(shell cygpath "$(TFDIR)/bazel-bin/tensorflow/lite/libtensorflowlite.so.if.lib")
 LINK_PATH_STT :=
 CFLAGS_STT    := -nologo -Fe$(STT_BIN)
 SOX_CFLAGS      :=
@@ -185,7 +185,7 @@ define copy_missing_libs
             new_missing="$$( (for f in $$(otool -L $$lib 2>/dev/null | tail -n +2 | awk '{ print $$1 }' | grep -v '$$lib'); do ls -hal $$f; done;) 2>&1 | grep 'No such' | cut -d':' -f2 | xargs basename -a)"; \
             missing_libs="$$missing_libs $$new_missing"; \
     elif [ "$(OS)" = "${CI_MSYS_VERSION}" ]; then \
-            missing_libs="libstt.so libkenlm.so"; \
+            missing_libs="libstt.so libkenlm.so libtensorflowlite.so"; \
         else \
             missing_libs="$$missing_libs $$($(LDD) $$lib | grep 'not found' | awk '{ print $$1 }')"; \
         fi; \

native_client/javascript/binding.gyp

@@ -27,12 +27,14 @@
                         "libraries": [
                             "../../../tensorflow/bazel-bin/native_client/libstt.so.if.lib",
                             "../../../tensorflow/bazel-bin/native_client/libkenlm.so.if.lib",
+                            "../../../tensorflow/bazel-bin/tensorflow/lite/libtensorflowlite.so.if.lib",
                         ],
                     },
                     {
                         "libraries": [
                             "../../../tensorflow/bazel-bin/native_client/libstt.so",
                             "../../../tensorflow/bazel-bin/native_client/libkenlm.so",
+                            "../../../tensorflow/bazel-bin/tensorflow/lite/libtensorflowlite.so",
                         ],
                     },
                 ],

native_client/stt.cc

@@ -14,13 +14,7 @@
 #include "modelstate.h"
 
 #include "workspace_status.h"
-
-#ifndef USE_TFLITE
-#include "tfmodelstate.h"
-#else
 #include "tflitemodelstate.h"
-#endif // USE_TFLITE
-
 #include "ctcdecode/ctc_beam_search_decoder.h"
 
 #ifdef __ANDROID__
@@ -282,13 +276,7 @@ STT_CreateModel(const char* aModelPath,
     return STT_ERR_NO_MODEL;
   }
 
-  std::unique_ptr<ModelState> model(
+  std::unique_ptr<ModelState> model(new TFLiteModelState());
-#ifndef USE_TFLITE
-    new TFModelState()
-#else
-    new TFLiteModelState()
-#endif
-  );
 
   if (!model) {
     std::cerr << "Could not allocate model state." << std::endl;

native_client/tfmodelstate.cc

@@ -1,263 +0,0 @@
-#include "tfmodelstate.h"
-
-#include "workspace_status.h"
-
-using namespace tensorflow;
-using std::vector;
-
-TFModelState::TFModelState()
-  : ModelState()
-  , mmap_env_(nullptr)
-  , session_(nullptr)
-{
-}
-
-TFModelState::~TFModelState()
-{
-  if (session_) {
-    Status status = session_->Close();
-    if (!status.ok()) {
-      std::cerr << "Error closing TensorFlow session: " << status << std::endl;
-    }
-  }
-}
-
-int
-TFModelState::init(const char* model_path)
-{
-  int err = ModelState::init(model_path);
-  if (err != STT_ERR_OK) {
-    return err;
-  }
-
-  Status status;
-  SessionOptions options;
-
-  mmap_env_.reset(new MemmappedEnv(Env::Default()));
-
-  bool is_mmap = std::string(model_path).find(".pbmm") != std::string::npos;
-  if (!is_mmap) {
-    std::cerr << "Warning: reading entire model file into memory. Transform model file into an mmapped graph to reduce heap usage." << std::endl;
-  } else {
-    status = mmap_env_->InitializeFromFile(model_path);
-    if (!status.ok()) {
-      std::cerr << status << std::endl;
-      return STT_ERR_FAIL_INIT_MMAP;
-    }
-
-    options.config.mutable_graph_options()
-      ->mutable_optimizer_options()
-      ->set_opt_level(::OptimizerOptions::L0);
-    options.env = mmap_env_.get();
-  }
-
-  Session* session;
-  status = NewSession(options, &session);
-  if (!status.ok()) {
-    std::cerr << status << std::endl;
-    return STT_ERR_FAIL_INIT_SESS;
-  }
-  session_.reset(session);
-
-  if (is_mmap) {
-    status = ReadBinaryProto(mmap_env_.get(),
-                             MemmappedFileSystem::kMemmappedPackageDefaultGraphDef,
-                             &graph_def_);
-  } else {
-    status = ReadBinaryProto(Env::Default(), model_path, &graph_def_);
-  }
-  if (!status.ok()) {
-    std::cerr << status << std::endl;
-    return STT_ERR_FAIL_READ_PROTOBUF;
-  }
-
-  status = session_->Create(graph_def_);
-  if (!status.ok()) {
-    std::cerr << status << std::endl;
-    return STT_ERR_FAIL_CREATE_SESS;
-  }
-
-  std::vector<tensorflow::Tensor> version_output;
-  status = session_->Run({}, {
-    "metadata_version"
-  }, {}, &version_output);
-  if (!status.ok()) {
-    std::cerr << "Unable to fetch graph version: " << status << std::endl;
-    return STT_ERR_MODEL_INCOMPATIBLE;
-  }
-
-  int graph_version = version_output[0].scalar<int>()();
-  if (graph_version < ds_graph_version()) {
-    std::cerr << "Specified model file version (" << graph_version << ") is "
-              << "incompatible with minimum version supported by this client ("
-              << ds_graph_version() << "). See "
-              << "https://stt.readthedocs.io/en/latest/USING.html#model-compatibility "
-              << "for more information" << std::endl;
-    return STT_ERR_MODEL_INCOMPATIBLE;
-  }
-
-  std::vector<tensorflow::Tensor> metadata_outputs;
-  status = session_->Run({}, {
-    "metadata_sample_rate",
-    "metadata_feature_win_len",
-    "metadata_feature_win_step",
-    "metadata_beam_width",
-    "metadata_alphabet",
-  }, {}, &metadata_outputs);
-  if (!status.ok()) {
-    std::cout << "Unable to fetch metadata: " << status << std::endl;
-    return STT_ERR_MODEL_INCOMPATIBLE;
-  }
-
-  sample_rate_ = metadata_outputs[0].scalar<int>()();
-  int win_len_ms = metadata_outputs[1].scalar<int>()();
-  int win_step_ms = metadata_outputs[2].scalar<int>()();
-  audio_win_len_ = sample_rate_ * (win_len_ms / 1000.0);
-  audio_win_step_ = sample_rate_ * (win_step_ms / 1000.0);
-  int beam_width = metadata_outputs[3].scalar<int>()();
-  beam_width_ = (unsigned int)(beam_width);
-
-  string serialized_alphabet = metadata_outputs[4].scalar<tensorflow::tstring>()();
-  err = alphabet_.Deserialize(serialized_alphabet.data(), serialized_alphabet.size());
-  if (err != 0) {
-    return STT_ERR_INVALID_ALPHABET;
-  }
-
-  assert(sample_rate_ > 0);
-  assert(audio_win_len_ > 0);
-  assert(audio_win_step_ > 0);
-  assert(beam_width_ > 0);
-  assert(alphabet_.GetSize() > 0);
-
-  for (int i = 0; i < graph_def_.node_size(); ++i) {
-    NodeDef node = graph_def_.node(i);
-    if (node.name() == "input_node") {
-      const auto& shape = node.attr().at("shape").shape();
-      n_steps_ = shape.dim(1).size();
-      n_context_ = (shape.dim(2).size()-1)/2;
-      n_features_ = shape.dim(3).size();
-      mfcc_feats_per_timestep_ = shape.dim(2).size() * shape.dim(3).size();
-    } else if (node.name() == "previous_state_c") {
-      const auto& shape = node.attr().at("shape").shape();
-      state_size_ = shape.dim(1).size();
-    } else if (node.name() == "logits_shape") {
-      Tensor logits_shape = Tensor(DT_INT32, TensorShape({3}));
-      if (!logits_shape.FromProto(node.attr().at("value").tensor())) {
-        continue;
-      }
-
-      int final_dim_size = logits_shape.vec<int>()(2) - 1;
-      if (final_dim_size != alphabet_.GetSize()) {
-        std::cerr << "Error: Alphabet size does not match loaded model: alphabet "
-                  << "has size " << alphabet_.GetSize()
-                  << ", but model has " << final_dim_size
-                  << " classes in its output. Make sure you're passing an alphabet "
-                  << "file with the same size as the one used for training."
-                  << std::endl;
-        return STT_ERR_INVALID_ALPHABET;
-      }
-    }
-  }
-
-  if (n_context_ == -1 || n_features_ == -1) {
-    std::cerr << "Error: Could not infer input shape from model file. "
-              << "Make sure input_node is a 4D tensor with shape "
-              << "[batch_size=1, time, window_size, n_features]."
-              << std::endl;
-    return STT_ERR_INVALID_SHAPE;
-  }
-
-  return STT_ERR_OK;
-}
-
-Tensor
-tensor_from_vector(const std::vector<float>& vec, const TensorShape& shape)
-{
-  Tensor ret(DT_FLOAT, shape);
-  auto ret_mapped = ret.flat<float>();
-  int i;
-  for (i = 0; i < vec.size(); ++i) {
-    ret_mapped(i) = vec[i];
-  }
-  for (; i < shape.num_elements(); ++i) {
-    ret_mapped(i) = 0.f;
-  }
-  return ret;
-}
-
-void
-copy_tensor_to_vector(const Tensor& tensor, vector<float>& vec, int num_elements = -1)
-{
-  auto tensor_mapped = tensor.flat<float>();
-  if (num_elements == -1) {
-    num_elements = tensor.shape().num_elements();
-  }
-  for (int i = 0; i < num_elements; ++i) {
-    vec.push_back(tensor_mapped(i));
-  }
-}
-
-void
-TFModelState::infer(const std::vector<float>& mfcc,
-                    unsigned int n_frames,
-                    const std::vector<float>& previous_state_c,
-                    const std::vector<float>& previous_state_h,
-                    vector<float>& logits_output,
-                    vector<float>& state_c_output,
-                    vector<float>& state_h_output)
-{
-  const size_t num_classes = alphabet_.GetSize() + 1; // +1 for blank
-
-  Tensor input = tensor_from_vector(mfcc, TensorShape({BATCH_SIZE, n_steps_, 2*n_context_+1, n_features_}));
-  Tensor previous_state_c_t = tensor_from_vector(previous_state_c, TensorShape({BATCH_SIZE, (long long)state_size_}));
-  Tensor previous_state_h_t = tensor_from_vector(previous_state_h, TensorShape({BATCH_SIZE, (long long)state_size_}));
-
-  Tensor input_lengths(DT_INT32, TensorShape({1}));
-  input_lengths.scalar<int>()() = n_frames;
-
-  vector<Tensor> outputs;
-  Status status = session_->Run(
-    {
-     {"input_node", input},
-     {"input_lengths", input_lengths},
-     {"previous_state_c", previous_state_c_t},
-     {"previous_state_h", previous_state_h_t}
-    },
-    {"logits", "new_state_c", "new_state_h"},
-    {},
-    &outputs);
-
-  if (!status.ok()) {
-    std::cerr << "Error running session: " << status << "\n";
-    return;
-  }
-
-  copy_tensor_to_vector(outputs[0], logits_output, n_frames * BATCH_SIZE * num_classes);
-
-  state_c_output.clear();
-  state_c_output.reserve(state_size_);
-  copy_tensor_to_vector(outputs[1], state_c_output);
-
-  state_h_output.clear();
-  state_h_output.reserve(state_size_);
-  copy_tensor_to_vector(outputs[2], state_h_output);
-}
-
-void
-TFModelState::compute_mfcc(const vector<float>& samples, vector<float>& mfcc_output)
-{
-  Tensor input = tensor_from_vector(samples, TensorShape({audio_win_len_}));
-
-  vector<Tensor> outputs;
-  Status status = session_->Run({{"input_samples", input}}, {"mfccs"}, {}, &outputs);
-
-  if (!status.ok()) {
-    std::cerr << "Error running session: " << status << "\n";
-    return;
-  }
-
-  // The feature computation graph is hardcoded to one audio length for now
-  const int n_windows = 1;
-  assert(outputs[0].shape().num_elements() / n_features_ == n_windows);
-  copy_tensor_to_vector(outputs[0], mfcc_output);
-}

native_client/tfmodelstate.h

@@ -1,35 +0,0 @@
-#ifndef TFMODELSTATE_H
-#define TFMODELSTATE_H
-
-#include <vector>
-
-#include "tensorflow/core/public/session.h"
-#include "tensorflow/core/platform/env.h"
-#include "tensorflow/core/util/memmapped_file_system.h"
-
-#include "modelstate.h"
-
-struct TFModelState : public ModelState
-{
-  std::unique_ptr<tensorflow::MemmappedEnv> mmap_env_;
-  std::unique_ptr<tensorflow::Session> session_;
-  tensorflow::GraphDef graph_def_;
-
-  TFModelState();
-  virtual ~TFModelState();
-
-  virtual int init(const char* model_path) override;
-
-  virtual void infer(const std::vector<float>& mfcc,
-                     unsigned int n_frames,
-                     const std::vector<float>& previous_state_c,
-                     const std::vector<float>& previous_state_h,
-                     std::vector<float>& logits_output,
-                     std::vector<float>& state_c_output,
-                     std::vector<float>& state_h_output) override;
-
-  virtual void compute_mfcc(const std::vector<float>& audio_buffer,
-                            std::vector<float>& mfcc_output) override;
-};
-
-#endif // TFMODELSTATE_H