piyushghai commented on a change in pull request #11626: [MXNET-651] MXNet Model Backwards Compatibility Checker URL: https://github.com/apache/incubator-mxnet/pull/11626#discussion_r202412563
########## File path: tests/nightly/model_backwards_compatibility_check/model_backwards_compat_train.py ########## @@ -0,0 +1,159 @@ +#!/usr/bin/env python + +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + +from common import * + +def train_module_checkpoint_api(): + model_name = 'module_checkpoint_api' + print ('Saving files for model %s' %model_name) + ### Prepare data + test_data = mx.nd.array(np.random.uniform(-1, 1, size=(20, 1))) + test_label = mx.nd.array(np.random.randint(0, 2, size=(20,)), dtype='float32') + data_iter = mx.io.NDArrayIter(test_data, test_label, batch_size=10) + + + mod = get_module_api_model_definition() + mod.bind(data_shapes=data_iter.provide_data, label_shapes=data_iter.provide_label) + weights = mx.initializer.Xavier(magnitude = 2.57) + mod.init_params(weights) + + mod.save_checkpoint(model_name, 1) + ### Save the data, labels + save_data_and_labels(test_data, test_label, model_name) + upload_data_and_labels_to_s3(model_name) + + inference_results = mod.predict(data_iter) + ### Save inference_results + save_inference_results(inference_results, model_name) + ### upload model and inference files to S3 + files = list() + files.append(model_name + '-0001.params') + files.append(model_name + '-symbol.json') + files.append(model_name + '-inference') + + mxnet_folder = str(mxnet_version) + backslash + model_name + backslash + + upload_model_files_to_s3(files, mxnet_folder) + + clean_model_files(files, model_name) + +def train_lenet_gluon_save_params_api(): + model_name = 'lenet_gluon_save_params_api' + print ('Saving files for model %s' %model_name) + net = Net() + weights = mx.initializer.Xavier(magnitude = 2.57) + net.initialize(weights, ctx = [mx.cpu(0)]) + ### Prepare data + + test_data = mx.nd.array(np.random.uniform(-1, 1, size=(20, 1, 30, 30))) + output = net(test_data) + # print (y) + # ### Save the test data as well. + # ### Save the inference output ys + # ### Save the model params + + mx.nd.save(model_name + '-data', {'data' : test_data}) + save_inference_results(output, model_name) + net.save_params(model_name + '-params') + + mxnet_folder = str(mxnet_version) + backslash + model_name + backslash + + files = list() + files.append(model_name + '-data') + files.append(model_name + '-inference') + files.append(model_name + '-params') + + upload_data_and_labels_to_s3(model_name) + + upload_model_files_to_s3(files, mxnet_folder) + + clean_model_files(files, model_name) + +def train_lenet_gluon_hybrid_export_api(): + model_name = 'lenet_gluon_hybrid_export_api' + print ('Saving files for model %s' %model_name) + net = HybridNet() + weights = mx.initializer.Xavier(magnitude = 2.57) + net.initialize(weights, ctx = [mx.cpu(0)]) + net.hybridize() + ### Prepare data + test_data = mx.nd.array(np.random.uniform(-1, 1, size=(20, 1, 30, 30))) + output = net(test_data) + # print (y) + ### Save the test data as well. + ### Save the inference output ys + ### Save the model params + + mx.nd.save(model_name + '-data', {'data' : test_data}) + save_inference_results(output, model_name) + net.export(model_name, epoch=1) + + mxnet_folder = str(mxnet_version) + backslash + model_name + backslash + + files = list() + files.append(model_name + '-data') + files.append(model_name + '-inference') + files.append(model_name + '-0001.params') + files.append(model_name + '-symbol.json') + + + upload_data_and_labels_to_s3(model_name) + + upload_model_files_to_s3(files, mxnet_folder) + + clean_model_files(files, model_name) + +def train_lstm_gluon_save_parameters_api(): + ## If this code is being run on version >= 1.2.0 only then execute it, since it uses save_parameters and load_parameters API + if compare_versions(str(mxnet_version), '1.2.1') < 0: + print ('Found MXNet version %s and exiting because this version does not contain save_parameters and load_parameters functions' %str(mxnet_version)) + sys.exit(1) Review comment: My bad. It should have been return. Will update it. ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
