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August 17, 2019 01:58
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tensor2tesnor tests
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| { | |
| "nbformat": 4, | |
| "nbformat_minor": 0, | |
| "metadata": { | |
| "colab": { | |
| "name": "tensor2tesnor.ipynb", | |
| "version": "0.3.2", | |
| "provenance": [] | |
| }, | |
| "kernelspec": { | |
| "name": "python3", | |
| "display_name": "Python 3" | |
| } | |
| }, | |
| "cells": [ | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "HeeXYtyF-yz5", | |
| "colab_type": "code", | |
| "outputId": "82f1ad29-4b87-4b32-9cfd-09887ce56f75", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 1000 | |
| } | |
| }, | |
| "source": [ | |
| "!pip install tensorflow-serving-api\n", | |
| "!pip install tensor2tensor" | |
| ], | |
| "execution_count": 2, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "Collecting tensorflow-serving-api\n", | |
| "\u001b[?25l Downloading https://files.pythonhosted.org/packages/24/c1/2b4ca53d699d79937c43d618de76f47db794364aeb3069349d97777678af/tensorflow_serving_api-1.14.0-py2.py3-none-any.whl (40kB)\n", | |
| "\u001b[K |████████████████████████████████| 40kB 3.0MB/s \n", | |
| "\u001b[?25hRequirement already satisfied: grpcio>=1.0<2 in /usr/local/lib/python3.6/dist-packages (from tensorflow-serving-api) (1.15.0)\n", | |
| "Requirement already satisfied: tensorflow~=1.14.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-serving-api) (1.14.0)\n", | |
| "Requirement already satisfied: protobuf>=3.6.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-serving-api) (3.7.1)\n", | |
| "Requirement already satisfied: six>=1.5.2 in /usr/local/lib/python3.6/dist-packages (from grpcio>=1.0<2->tensorflow-serving-api) (1.12.0)\n", | |
| "Requirement already satisfied: tensorboard<1.15.0,>=1.14.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow~=1.14.0->tensorflow-serving-api) (1.14.0)\n", | |
| "Requirement already satisfied: wrapt>=1.11.1 in /usr/local/lib/python3.6/dist-packages (from tensorflow~=1.14.0->tensorflow-serving-api) (1.11.2)\n", | |
| "Requirement already satisfied: wheel>=0.26 in /usr/local/lib/python3.6/dist-packages (from tensorflow~=1.14.0->tensorflow-serving-api) (0.33.4)\n", | |
| "Requirement already satisfied: tensorflow-estimator<1.15.0rc0,>=1.14.0rc0 in /usr/local/lib/python3.6/dist-packages (from tensorflow~=1.14.0->tensorflow-serving-api) (1.14.0)\n", | |
| "Requirement already satisfied: google-pasta>=0.1.6 in /usr/local/lib/python3.6/dist-packages (from tensorflow~=1.14.0->tensorflow-serving-api) (0.1.7)\n", | |
| "Requirement already satisfied: numpy<2.0,>=1.14.5 in /usr/local/lib/python3.6/dist-packages (from tensorflow~=1.14.0->tensorflow-serving-api) (1.16.4)\n", | |
| "Requirement already satisfied: termcolor>=1.1.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow~=1.14.0->tensorflow-serving-api) (1.1.0)\n", | |
| "Requirement already satisfied: gast>=0.2.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow~=1.14.0->tensorflow-serving-api) (0.2.2)\n", | |
| "Requirement already satisfied: absl-py>=0.7.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow~=1.14.0->tensorflow-serving-api) (0.7.1)\n", | |
| "Requirement already satisfied: keras-preprocessing>=1.0.5 in /usr/local/lib/python3.6/dist-packages (from tensorflow~=1.14.0->tensorflow-serving-api) (1.1.0)\n", | |
| "Requirement already satisfied: keras-applications>=1.0.6 in /usr/local/lib/python3.6/dist-packages (from tensorflow~=1.14.0->tensorflow-serving-api) (1.0.8)\n", | |
| "Requirement already satisfied: astor>=0.6.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow~=1.14.0->tensorflow-serving-api) (0.8.0)\n", | |
| "Requirement already satisfied: setuptools in /usr/local/lib/python3.6/dist-packages (from protobuf>=3.6.0->tensorflow-serving-api) (41.0.1)\n", | |
| "Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.6/dist-packages (from tensorboard<1.15.0,>=1.14.0->tensorflow~=1.14.0->tensorflow-serving-api) (3.1.1)\n", | |
| "Requirement already satisfied: werkzeug>=0.11.15 in /usr/local/lib/python3.6/dist-packages (from tensorboard<1.15.0,>=1.14.0->tensorflow~=1.14.0->tensorflow-serving-api) (0.15.5)\n", | |
| "Requirement already satisfied: h5py in /usr/local/lib/python3.6/dist-packages (from keras-applications>=1.0.6->tensorflow~=1.14.0->tensorflow-serving-api) (2.8.0)\n", | |
| "Installing collected packages: tensorflow-serving-api\n", | |
| "Successfully installed tensorflow-serving-api-1.14.0\n", | |
| "Requirement already satisfied: tensor2tensor in /usr/local/lib/python3.6/dist-packages (1.11.0)\n", | |
| "Requirement already satisfied: flask in /usr/local/lib/python3.6/dist-packages (from tensor2tensor) (1.1.1)\n", | |
| "Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from tensor2tensor) (1.12.0)\n", | |
| "Requirement already satisfied: google-api-python-client in /usr/local/lib/python3.6/dist-packages (from tensor2tensor) (1.7.10)\n", | |
| "Requirement already satisfied: tqdm in /usr/local/lib/python3.6/dist-packages (from tensor2tensor) (4.28.1)\n", | |
| "Requirement already satisfied: h5py in /usr/local/lib/python3.6/dist-packages (from tensor2tensor) (2.8.0)\n", | |
| "Requirement already satisfied: mesh-tensorflow in /usr/local/lib/python3.6/dist-packages (from tensor2tensor) (0.0.5)\n", | |
| "Requirement already satisfied: gym in /usr/local/lib/python3.6/dist-packages (from tensor2tensor) (0.10.11)\n", | |
| "Requirement already satisfied: numpy in /usr/local/lib/python3.6/dist-packages (from tensor2tensor) (1.16.4)\n", | |
| "Requirement already satisfied: bz2file in /usr/local/lib/python3.6/dist-packages (from tensor2tensor) (0.98)\n", | |
| "Requirement already satisfied: gevent in /usr/local/lib/python3.6/dist-packages (from tensor2tensor) (1.4.0)\n", | |
| "Requirement already satisfied: gunicorn in /usr/local/lib/python3.6/dist-packages (from tensor2tensor) (19.9.0)\n", | |
| "Requirement already satisfied: sympy in /usr/local/lib/python3.6/dist-packages (from tensor2tensor) (1.1.1)\n", | |
| "Requirement already satisfied: scipy in /usr/local/lib/python3.6/dist-packages (from tensor2tensor) (1.3.1)\n", | |
| "Requirement already satisfied: requests in /usr/local/lib/python3.6/dist-packages (from tensor2tensor) (2.21.0)\n", | |
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| "Requirement already satisfied: future in /usr/local/lib/python3.6/dist-packages (from tensor2tensor) (0.16.0)\n", | |
| "Requirement already satisfied: oauth2client in /usr/local/lib/python3.6/dist-packages (from tensor2tensor) (4.1.3)\n", | |
| "Requirement already satisfied: tfds-nightly in /usr/local/lib/python3.6/dist-packages (from tensor2tensor) (1.1.0.dev201908090105)\n", | |
| "Requirement already satisfied: click>=5.1 in /usr/local/lib/python3.6/dist-packages (from flask->tensor2tensor) (7.0)\n", | |
| "Requirement already satisfied: Jinja2>=2.10.1 in /usr/local/lib/python3.6/dist-packages (from flask->tensor2tensor) (2.10.1)\n", | |
| "Requirement already satisfied: Werkzeug>=0.15 in /usr/local/lib/python3.6/dist-packages (from flask->tensor2tensor) (0.15.5)\n", | |
| "Requirement already satisfied: itsdangerous>=0.24 in /usr/local/lib/python3.6/dist-packages (from flask->tensor2tensor) (1.1.0)\n", | |
| "Requirement already satisfied: google-auth-httplib2>=0.0.3 in /usr/local/lib/python3.6/dist-packages (from google-api-python-client->tensor2tensor) (0.0.3)\n", | |
| "Requirement already satisfied: httplib2<1dev,>=0.9.2 in /usr/local/lib/python3.6/dist-packages (from google-api-python-client->tensor2tensor) (0.11.3)\n", | |
| "Requirement already satisfied: google-auth>=1.4.1 in /usr/local/lib/python3.6/dist-packages (from google-api-python-client->tensor2tensor) (1.4.2)\n", | |
| "Requirement already satisfied: uritemplate<4dev,>=3.0.0 in /usr/local/lib/python3.6/dist-packages (from google-api-python-client->tensor2tensor) (3.0.0)\n", | |
| "Requirement already satisfied: pyglet>=1.2.0 in /usr/local/lib/python3.6/dist-packages (from gym->tensor2tensor) (1.4.1)\n", | |
| "Requirement already satisfied: greenlet>=0.4.14; platform_python_implementation == \"CPython\" in /usr/local/lib/python3.6/dist-packages (from gevent->tensor2tensor) (0.4.15)\n", | |
| "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.6/dist-packages (from sympy->tensor2tensor) (1.1.0)\n", | |
| "Requirement already satisfied: idna<2.9,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests->tensor2tensor) (2.8)\n", | |
| "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests->tensor2tensor) (2019.6.16)\n", | |
| "Requirement already satisfied: urllib3<1.25,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests->tensor2tensor) (1.24.3)\n", | |
| "Requirement already satisfied: chardet<3.1.0,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests->tensor2tensor) (3.0.4)\n", | |
| "Requirement already satisfied: cloudpickle>=0.6.1 in /usr/local/lib/python3.6/dist-packages (from tensorflow-probability->tensor2tensor) (0.6.1)\n", | |
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| "Requirement already satisfied: rsa>=3.1.4 in /usr/local/lib/python3.6/dist-packages (from oauth2client->tensor2tensor) (4.0)\n", | |
| "Requirement already satisfied: pyasn1>=0.1.7 in /usr/local/lib/python3.6/dist-packages (from oauth2client->tensor2tensor) (0.4.6)\n", | |
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| "Requirement already satisfied: psutil in /usr/local/lib/python3.6/dist-packages (from tfds-nightly->tensor2tensor) (5.4.8)\n", | |
| "Requirement already satisfied: attrs in /usr/local/lib/python3.6/dist-packages (from tfds-nightly->tensor2tensor) (19.1.0)\n", | |
| "Requirement already satisfied: termcolor in /usr/local/lib/python3.6/dist-packages (from tfds-nightly->tensor2tensor) (1.1.0)\n", | |
| "Requirement already satisfied: promise in /usr/local/lib/python3.6/dist-packages (from tfds-nightly->tensor2tensor) (2.2.1)\n", | |
| "Requirement already satisfied: absl-py in /usr/local/lib/python3.6/dist-packages (from tfds-nightly->tensor2tensor) (0.7.1)\n", | |
| "Requirement already satisfied: wrapt in /usr/local/lib/python3.6/dist-packages (from tfds-nightly->tensor2tensor) (1.11.2)\n", | |
| "Requirement already satisfied: dill in /usr/local/lib/python3.6/dist-packages (from tfds-nightly->tensor2tensor) (0.3.0)\n", | |
| "Requirement already satisfied: tensorflow-metadata in /usr/local/lib/python3.6/dist-packages (from tfds-nightly->tensor2tensor) (0.14.0)\n", | |
| "Requirement already satisfied: MarkupSafe>=0.23 in /usr/local/lib/python3.6/dist-packages (from Jinja2>=2.10.1->flask->tensor2tensor) (1.1.1)\n", | |
| "Requirement already satisfied: cachetools>=2.0.0 in /usr/local/lib/python3.6/dist-packages (from google-auth>=1.4.1->google-api-python-client->tensor2tensor) (3.1.1)\n", | |
| "Requirement already satisfied: setuptools in /usr/local/lib/python3.6/dist-packages (from protobuf>=3.6.1->tfds-nightly->tensor2tensor) (41.0.1)\n", | |
| "Requirement already satisfied: googleapis-common-protos in /usr/local/lib/python3.6/dist-packages (from tensorflow-metadata->tfds-nightly->tensor2tensor) (1.6.0)\n" | |
| ], | |
| "name": "stdout" | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "IkWcrHEZ-z9B", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "# t2t-query-server \\\n", | |
| "# --server=localhost:9000 \\\n", | |
| "# --servable_name=my_model \\\n", | |
| "# --problem=translate_ende_wmt8k \\\n", | |
| "# --data_dir=~/t2t/data" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "tb3GSo22AOIL", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "import requests\n", | |
| "import json" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "LY47_KBnAUlu", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "MUp4Ou46IqyK", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "from __future__ import absolute_import\n", | |
| "from __future__ import division\n", | |
| "from __future__ import print_function\n", | |
| "\n", | |
| "import os\n", | |
| "\n", | |
| "from oauth2client.client import GoogleCredentials\n", | |
| "from six.moves import input # pylint: disable=redefined-builtin\n", | |
| "\n", | |
| "from tensor2tensor import problems as problems_lib # pylint: disable=unused-import\n", | |
| "from tensor2tensor.serving import serving_utils\n", | |
| "from tensor2tensor.utils import registry\n", | |
| "from tensor2tensor.utils import usr_dir\n", | |
| "import tensorflow as tf\n", | |
| "\n", | |
| "\n", | |
| "from tensor2tensor.data_generators import text_encoder\n", | |
| "\n" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "brBk1y0ZMC2h", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "import numpy as np" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "_3t6IoebOVic", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "problem_name='summarize_cnn_dailymail32k'\n", | |
| "problem = registry.problem(problem_name)" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "JVk6e-SOKvnk", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "# encoder1=problem.feature_encoders(\"./\")[\"inputs\"]" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "PcbiuihHLCnd", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "# encoder2=problem.feature_info[fname].encoder" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "XWBIQo58LOKY", | |
| "colab_type": "code", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 34 | |
| }, | |
| "outputId": "f803bf10-3e07-443c-d505-7816ab62eaba" | |
| }, | |
| "source": [ | |
| "input_text=\"testing our model\"\n", | |
| "inputs_list=[input_text]\n" | |
| ], | |
| "execution_count": 76, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "'{ \"instances\" : [[[2807],\\n [ 149],\\n [1146]]] }'" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 76 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "FWUpK52mO0vq", | |
| "colab_type": "code", | |
| "outputId": "b722d69c-ba13-4175-c701-4a8c23105fff", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 275 | |
| } | |
| }, | |
| "source": [ | |
| "!mkdir tmp\n", | |
| "!mkdir data\n", | |
| "!wget \"https://storage.googleapis.com/tensor2tensor-data/vocab.summarize_cnn_dailymail32k.32768.subwords\"\n" | |
| ], | |
| "execution_count": 19, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "mkdir: cannot create directory ‘tmp’: File exists\n", | |
| "mkdir: cannot create directory ‘data’: File exists\n", | |
| "--2019-08-17 00:47:45-- https://storage.googleapis.com/tensor2tensor-data/vocab.summarize_cnn_dailymail32k.32768.subwords\n", | |
| "Resolving storage.googleapis.com (storage.googleapis.com)... 74.125.141.128, 2607:f8b0:400c:c06::80\n", | |
| "Connecting to storage.googleapis.com (storage.googleapis.com)|74.125.141.128|:443... connected.\n", | |
| "HTTP request sent, awaiting response... 200 OK\n", | |
| "Length: 300745 (294K) [application/octet-stream]\n", | |
| "Saving to: ‘vocab.summarize_cnn_dailymail32k.32768.subwords.1’\n", | |
| "\n", | |
| "vocab.summarize_cnn 100%[===================>] 293.70K --.-KB/s in 0.003s \n", | |
| "\n", | |
| "2019-08-17 00:47:45 (101 MB/s) - ‘vocab.summarize_cnn_dailymail32k.32768.subwords.1’ saved [300745/300745]\n", | |
| "\n" | |
| ], | |
| "name": "stdout" | |
| }, | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "HParams([('batch_size_multiplier', 1), ('input_space_id', 0), ('loss_multiplier', 1.0), ('modality', {'targets': <tensor2tensor.layers.modalities.SymbolModality object at 0x7f28a556a4a8>, 'inputs': <tensor2tensor.layers.modalities.SymbolModality object at 0x7f28a556a3c8>}), ('stop_at_eos', 1), ('target_space_id', 0), ('vocabulary', {'targets': <tensor2tensor.data_generators.text_encoder.SubwordTextEncoder object at 0x7f28a5715940>, 'inputs': <tensor2tensor.data_generators.text_encoder.SubwordTextEncoder object at 0x7f28a5715940>}), ('was_copy', False), ('was_reversed', False)])" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 19 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "Aj_RRduLC7Dw", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "hparams = tf.contrib.training.HParams(\n", | |
| " data_dir=os.path.expanduser(\"./\"))\n", | |
| "problem.get_hparams(hparams)" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "94tiNeTLBmTX", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "# def _encode(inputs, encoder, add_eos=True):\n", | |
| "# input_ids = encoder.encode(inputs)\n", | |
| "# if add_eos:\n", | |
| "# input_ids.append(text_encoder.EOS_ID)\n", | |
| "# input_ids=tf.reshape(inputs, [1, -1, 1])\n", | |
| "# return input_ids\n" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "28AohVI3O1sa", | |
| "colab_type": "code", | |
| "outputId": "ae5da80d-6a51-403b-cebb-67daab42b267", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 187 | |
| } | |
| }, | |
| "source": [ | |
| "# fname = \"inputs\" if problem.has_inputs else \"targets\"\n", | |
| "# print(fname)\n", | |
| "# input_encoder = problem.feature_info[fname].encoder\n", | |
| "# print(input_encoder)\n", | |
| "# input_ids_list = [\n", | |
| "# _encode(inputs, input_encoder, add_eos=problem.has_inputs)\n", | |
| "# for inputs in inputs_list\n", | |
| "# ]\n", | |
| "# print(input_ids_list)\n", | |
| "# examples = [_make_example(input_ids, problem, fname)\n", | |
| "# for input_ids in input_ids_list]" | |
| ], | |
| "execution_count": 35, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "inputs\n", | |
| "<tensor2tensor.data_generators.text_encoder.SubwordTextEncoder object at 0x7f28a5715940>\n", | |
| "[[2807, 149, 1146, 1]]\n", | |
| "{'targets': VarLenFeature(dtype=tf.int64), 'inputs': VarLenFeature(dtype=tf.int64)} None\n", | |
| "targets\n", | |
| "VarLenFeature(dtype=tf.int64)\n", | |
| "<dtype: 'int64'>\n", | |
| "inputs\n", | |
| "VarLenFeature(dtype=tf.int64)\n", | |
| "<dtype: 'int64'>\n" | |
| ], | |
| "name": "stdout" | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "oDtI9kLmBjCZ", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "# examples" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "9RXA1mtWP9OT", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "J-06yCqFQ8eC", | |
| "colab_type": "code", | |
| "outputId": "d9f1a2f6-50df-4fba-9503-8d9d3d321769", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 224 | |
| } | |
| }, | |
| "source": [ | |
| "" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "--2019-08-16 17:07:39-- https://storage.googleapis.com/tensor2tensor-data/vocab.summarize_cnn_dailymail32k.32768.subwords\n", | |
| "Resolving storage.googleapis.com (storage.googleapis.com)... 74.125.141.128, 2607:f8b0:400c:c06::80\n", | |
| "Connecting to storage.googleapis.com (storage.googleapis.com)|74.125.141.128|:443... connected.\n", | |
| "HTTP request sent, awaiting response... 200 OK\n", | |
| "Length: 300745 (294K) [application/octet-stream]\n", | |
| "Saving to: ‘vocab.summarize_cnn_dailymail32k.32768.subwords’\n", | |
| "\n", | |
| "\r vocab.sum 0%[ ] 0 --.-KB/s \rvocab.summarize_cnn 100%[===================>] 293.70K --.-KB/s in 0.003s \n", | |
| "\n", | |
| "2019-08-16 17:07:39 (91.3 MB/s) - ‘vocab.summarize_cnn_dailymail32k.32768.subwords’ saved [300745/300745]\n", | |
| "\n" | |
| ], | |
| "name": "stdout" | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "NDxPWMYbRQ4y", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "# def _make_example(input_ids, problem, input_feature_name=\"inputs\"):\n", | |
| "# \"\"\"Make a tf.train.Example for the problem.\n", | |
| "# features[input_feature_name] = input_ids\n", | |
| "# Also fills in any other required features with dummy values.\n", | |
| "# Args:\n", | |
| "# input_ids: list<int>.\n", | |
| "# problem: Problem.\n", | |
| "# input_feature_name: name of feature for input_ids.\n", | |
| "# Returns:\n", | |
| "# tf.train.Example\n", | |
| "# \"\"\"\n", | |
| "# features = {\n", | |
| "# input_feature_name:\n", | |
| "# tf.train.Feature(int64_list=tf.train.Int64List(value=input_ids))\n", | |
| "# }\n", | |
| "\n", | |
| "# # Fill in dummy values for any other required features that presumably\n", | |
| "# # will not actually be used for prediction.\n", | |
| "# data_fields, _ = problem.example_reading_spec()\n", | |
| "# print(data_fields,_)\n", | |
| "# for fname, ftype in data_fields.items():\n", | |
| "# print(fname)\n", | |
| "# print(ftype)\n", | |
| "# print(ftype.dtype)\n", | |
| "# if fname == input_feature_name:\n", | |
| "# continue\n", | |
| "# if not isinstance(ftype, tf.FixedLenFeature):\n", | |
| "# # Only FixedLenFeatures are required\n", | |
| "# continue\n", | |
| "# if ftype.default_value is not None:\n", | |
| "# # If there's a default value, no need to fill it in\n", | |
| "# continue\n", | |
| "# num_elements = functools.reduce(lambda acc, el: acc * el, ftype.shape, 1)\n", | |
| "# if ftype.dtype in [tf.int32, tf.int64]:\n", | |
| "# value = tf.train.Feature(\n", | |
| "# int64_list=tf.train.Int64List(value=[0] * num_elements))\n", | |
| "# if ftype.dtype in [tf.float32, tf.float64]:\n", | |
| "# value = tf.train.Feature(\n", | |
| "# float_list=tf.train.FloatList(value=[0.] * num_elements))\n", | |
| "# if ftype.dtype == tf.bytes:\n", | |
| "# value = tf.train.Feature(\n", | |
| "# bytes_list=tf.train.BytesList(value=[\"\"] * num_elements))\n", | |
| "# tf.logging.info(\"Adding dummy value for feature %s as it is required by \"\n", | |
| "# \"the Problem.\", fname)\n", | |
| "# features[fname] = value\n", | |
| "# return tf.train.Example(features=tf.train.Features(feature=features))\n", | |
| "\n" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "qpSb_6SkRRlE", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "# r = requests.post('https://services.paperspace.io/model-serving/desfnnrqt1v633v:predict', json={\"instances\": examples[0]})\n", | |
| "# r.text" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "n9qxZk7QaiR0", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "# import base64\n", | |
| "\n", | |
| "# input_data = {\n", | |
| "# \"instances\": [{\n", | |
| "# \"input\": {\n", | |
| "# \"b64\": base64.b64encode(ex.SerializeToString())\n", | |
| "# }\n", | |
| "# } for ex in examples]\n", | |
| "# }" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "luRevhSNapW0", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "rXKBsH4icLtP", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "# r = requests.post('https://services.paperspace.io/model-serving/desfnnrqt1v633v:predict', json=input_data)\n", | |
| "# r.text" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "nwBwW1LXcPIM", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "# a=tf.contrib.util.make_tensor_proto(\n", | |
| "# [ex.SerializeToString() for ex in examples], shape=[len(examples)])" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "3EQV5RfpdHb2", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "# r = requests.post('https://services.paperspace.io/model-serving/desfnnrqt1v633v:predict', json={\"instances\": [\"\\n\\027\\n\\025\\n\\006inputs\\022\\013\\032\\t\\n\\007\\367\\025\\225\\001\\372\\010\\001\"]})\n", | |
| "# r.text" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "HBYaE9UedVz3", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "utyt23i0dX1n", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "# a=[ex.SerializeToString() for ex in examples]" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "w8teVfOndeC4", | |
| "colab_type": "code", | |
| "outputId": "aeccf4cd-1ff4-4b8d-dcb1-f224c08e881c", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 34 | |
| } | |
| }, | |
| "source": [ | |
| "input_ids_list" | |
| ], | |
| "execution_count": 107, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "[[2807, 149, 1146, 1]]" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 107 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "C7ZNCR0AdgJg", | |
| "colab_type": "code", | |
| "outputId": "b774f80a-be36-46ce-d161-abc5f02bc0e3", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 54 | |
| } | |
| }, | |
| "source": [ | |
| "json_request = '{{ \"instances\" : {} }}'.format(''.join([str(e) for e in input_ids_list]))\n", | |
| "json_request = '{{ \"instances\" : {} }}'.format(np.array2string(np.array(input_ids_list[0]), separator=',', formatter={'float':lambda x: \"%.1f\" % x}))\n", | |
| "r = requests.post('https://services.paperspace.io/model-serving/desfnnrqt1v633v:predict',data=json_request)\n", | |
| "r.text" | |
| ], | |
| "execution_count": 105, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "'{ \"error\": \"Failed to process element: 0 of \\\\\\'instances\\\\\\' list. Error: Invalid argument: JSON Value: 2807 Type: Number is not of expected type: string\" }'" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 105 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "ON_iKSvahBY5", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "-RkeUXSchPsz", | |
| "colab_type": "code", | |
| "outputId": "bb7b7f11-65e4-4eb6-9e01-c316024bc041", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 34 | |
| } | |
| }, | |
| "source": [ | |
| "r = requests.post('https://services.paperspace.io/model-serving/desfnnrqt1v633v:predict', \n", | |
| " json={\"instances\":[{\"input\":[['2807', '149', '1146', '1']]}]})\n", | |
| "r.text" | |
| ], | |
| "execution_count": 110, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "'{ \"error\": \"Incompatible shapes at component 0: expected [1,4] but got [].\\\\n\\\\t [[{{node TensorSliceDataset}}]]\" }'" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 110 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "KBbWGRo9jHDo", | |
| "colab_type": "code", | |
| "outputId": "04e82f50-4923-4da4-c19d-f0004188f15a", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 34 | |
| } | |
| }, | |
| "source": [ | |
| "r = requests.post('https://services.paperspace.io/model-serving/desfnnrqt1v633v:predict', \n", | |
| " json={\"instances\":[[\"2807\", \"149\", \"1146\"]]})\n", | |
| "r.text" | |
| ], | |
| "execution_count": 111, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "'{ \"error\": \"Incompatible shapes at component 0: expected [3] but got [].\\\\n\\\\t [[{{node TensorSliceDataset}}]]\" }'" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 111 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "TU99au7GID8O", | |
| "colab_type": "code", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 34 | |
| }, | |
| "outputId": "f4f7933e-9d8a-477a-9aff-1c815a8ae860" | |
| }, | |
| "source": [ | |
| "r = requests.post('https://services.paperspace.io/model-serving/desfnnrqt1v633v:predict', \n", | |
| " json={\"instances\":[[[\"2807\"], [\"149\"], [\"1146\"]]]})\n", | |
| "r.text" | |
| ], | |
| "execution_count": 112, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "'{ \"error\": \"Incompatible shapes at component 0: expected [3,1] but got [].\\\\n\\\\t [[{{node TensorSliceDataset}}]]\" }'" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 112 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "u7-kRbLho3qP", | |
| "colab_type": "code", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 34 | |
| }, | |
| "outputId": "52be7859-4da1-4f26-fc55-23e153a92193" | |
| }, | |
| "source": [ | |
| "r = requests.post('https://services.paperspace.io/model-serving/desfnnrqt1v633v:predict', \n", | |
| " json={\"instances\":[[]]})\n", | |
| "r.text" | |
| ], | |
| "execution_count": 113, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "'{ \"error\": \"Incompatible shapes at component 0: expected [0] but got [].\\\\n\\\\t [[{{node TensorSliceDataset}}]]\" }'" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 113 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "dc5D8VjFIjot", | |
| "colab_type": "code", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 54 | |
| }, | |
| "outputId": "c7630e60-18d7-4713-bad4-344b6e52aef1" | |
| }, | |
| "source": [ | |
| "r = requests.post('https://services.paperspace.io/model-serving/desfnnrqt1v633v:predict', \n", | |
| " json={\"instances\":[[]]})\n", | |
| "r.text" | |
| ], | |
| "execution_count": 114, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "'{ \"error\": \"2 root error(s) found.\\\\n (0) Invalid argument: Incompatible shapes at component 0: expected [0] but got [].\\\\n\\\\t [[{{node TensorSliceDataset}}]]\\\\n (1) Invalid argument: Incompatible shapes at component 0: expected [0] but got [].\\\\n\\\\t [[{{node TensorSliceDataset}}]]\\\\n\\\\t [[transformer/Shape/_423]]\\\\n0 successful operations.\\\\n0 derived errors ignored.\" }'" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 114 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "pw31ijOPJq9d", | |
| "colab_type": "code", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 85 | |
| }, | |
| "outputId": "7f592bc6-9277-45c6-ebf7-0bd3e5713970" | |
| }, | |
| "source": [ | |
| "# tf.reshape(encoders[\"inputs\"].encode(input_str) + [1], [1, -1, 1, 1])\n", | |
| "\n", | |
| "inputs=encoder2.encode(input_text)\n", | |
| "inputs=np.array(inputs)\n", | |
| "inputs=np.reshape(inputs, [1, -1, 1])\n", | |
| "print(inputs)\n", | |
| "json_request = '{{ \"instances\" : {} }}'.format(np.array2string(inputs, separator=',', formatter={'int':lambda x: \"\\\"{}\\\"\".format(x)}))\n", | |
| "json_request" | |
| ], | |
| "execution_count": 115, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "[[[2807]\n", | |
| " [ 149]\n", | |
| " [1146]]]\n" | |
| ], | |
| "name": "stdout" | |
| }, | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "'{ \"instances\" : [[[\"2807\"],\\n [\"149\"],\\n [\"1146\"]]] }'" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 115 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "zSWTcvBHNFbO", | |
| "colab_type": "code", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 34 | |
| }, | |
| "outputId": "668f0e40-a6ba-4971-e71f-95ac8c619757" | |
| }, | |
| "source": [ | |
| "r = requests.post('https://services.paperspace.io/model-serving/desfnnrqt1v633v:predict', \n", | |
| " data=json_request)\n", | |
| "r.text" | |
| ], | |
| "execution_count": 117, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "'{ \"error\": \"Incompatible shapes at component 0: expected [3,1] but got [].\\\\n\\\\t [[{{node TensorSliceDataset}}]]\" }'" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 117 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "Zp48xE6ENIUh", | |
| "colab_type": "code", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 119 | |
| }, | |
| "outputId": "b13d1ea0-0ce9-4cc5-f239-b0c07e15db88" | |
| }, | |
| "source": [ | |
| "# tf.reshape(encoders[\"inputs\"].encode(input_str) + [1], [1, -1, 1, 1])\n", | |
| "\n", | |
| "inputs=encoder2.encode(input_text)\n", | |
| "# tf.reshape(inputs, [1, -1, 1])\n", | |
| "inputs=np.array(inputs)\n", | |
| "inputs=np.reshape(inputs, [1, -1, 1, 1])\n", | |
| "print(inputs)\n", | |
| "json_request = '{{ \"instances\" : {} }}'.format(np.array2string(inputs, separator=',', formatter={'int':lambda x: \"\\\"{}\\\"\".format(x)}))\n", | |
| "json_request" | |
| ], | |
| "execution_count": 118, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "[[[[2807]]\n", | |
| "\n", | |
| " [[ 149]]\n", | |
| "\n", | |
| " [[1146]]]]\n" | |
| ], | |
| "name": "stdout" | |
| }, | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "'{ \"instances\" : [[[[\"2807\"]],\\n\\n [[\"149\"]],\\n\\n [[\"1146\"]]]] }'" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 118 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "TERPIzIDOMDj", | |
| "colab_type": "code", | |
| "colab": { | |
| "base_uri": "https://localhost:8080/", | |
| "height": 34 | |
| }, | |
| "outputId": "03e43c26-868f-4a90-86dd-3d6b773302bf" | |
| }, | |
| "source": [ | |
| "r = requests.post('https://services.paperspace.io/model-serving/desfnnrqt1v633v:predict', \n", | |
| " data=json_request)\n", | |
| "r.text" | |
| ], | |
| "execution_count": 119, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/plain": [ | |
| "'{ \"error\": \"Incompatible shapes at component 0: expected [3,1,1] but got [].\\\\n\\\\t [[{{node TensorSliceDataset}}]]\" }'" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 119 | |
| } | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "metadata": { | |
| "id": "Gv0hWUvWR2L6", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "source": [ | |
| "" | |
| ], | |
| "execution_count": 0, | |
| "outputs": [] | |
| } | |
| ] | |
| } |
No, it does not. Misha said probably there is a problem with deployed model so I am not sure whats the problem. I will start from deploying model myself if I get time.
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"name": "tensor2tesnor.ipynb" -- typo on filename here matter?