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-rw-r--r--model-integration/src/test/models/tensorflow/external/Model_A/optimized_v2/saved_model.pbtxt1368
-rw-r--r--model-integration/src/test/models/tensorflow/external/Model_B/factorization_machine_v1/export/optimized/saved_model.pbtxt1368
-rw-r--r--model-integration/src/test/models/tensorflow/external/Model_B/factorization_machine_v1/export/standard/saved_model.pbtxt11403
-rw-r--r--model-integration/src/test/models/tensorflow/external/Model_B/factorization_machine_v1/export/standard/variables/variables.data-00000-of-00001bin48 -> 0 bytes
-rw-r--r--model-integration/src/test/models/tensorflow/external/Model_B/factorization_machine_v1/export/standard/variables/variables.indexbin393 -> 0 bytes
-rw-r--r--model-integration/src/test/models/tensorflow/external/Model_C/factorization_machine_v1/export/optimized/saved_model.pbtxt959
-rw-r--r--model-integration/src/test/models/tensorflow/external/Model_C/factorization_machine_v1/export/standard/saved_model.pbtxt8622
-rw-r--r--model-integration/src/test/models/tensorflow/external/Model_C/factorization_machine_v1/export/standard/variables/variables.data-00000-of-00001bin24 -> 0 bytes
-rw-r--r--model-integration/src/test/models/tensorflow/external/Model_C/factorization_machine_v1/export/standard/variables/variables.indexbin209 -> 0 bytes
-rw-r--r--model-integration/src/test/models/tensorflow/external/modelv1/saved_model.pbbin170845 -> 0 bytes
-rw-r--r--model-integration/src/test/models/tensorflow/external/modelv1/variables/variables.data-00000-of-00001bin56124 -> 0 bytes
-rw-r--r--model-integration/src/test/models/tensorflow/external/modelv1/variables/variables.indexbin896 -> 0 bytes
-rw-r--r--model-integration/src/test/models/tensorflow/external/modelv2/saved_model.pbbin194189 -> 0 bytes
-rw-r--r--model-integration/src/test/models/tensorflow/external/modelv2/variables/variables.data-00000-of-00001bin56932 -> 0 bytes
-rw-r--r--model-integration/src/test/models/tensorflow/external/modelv2/variables/variables.indexbin1046 -> 0 bytes
-rw-r--r--model-integration/src/test/models/tensorflow/external/train.py53
-rw-r--r--model-integration/src/test/models/tensorflow/external/train_embed.py66
17 files changed, 0 insertions, 23839 deletions
diff --git a/model-integration/src/test/models/tensorflow/external/Model_A/optimized_v2/saved_model.pbtxt b/model-integration/src/test/models/tensorflow/external/Model_A/optimized_v2/saved_model.pbtxt
deleted file mode 100644
index d2dc51ac328..00000000000
--- a/model-integration/src/test/models/tensorflow/external/Model_A/optimized_v2/saved_model.pbtxt
+++ /dev/null
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diff --git a/model-integration/src/test/models/tensorflow/external/Model_B/factorization_machine_v1/export/standard/variables/variables.data-00000-of-00001 b/model-integration/src/test/models/tensorflow/external/Model_B/factorization_machine_v1/export/standard/variables/variables.data-00000-of-00001
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- }
- }
- collection_def {
- key: "trainable_variables"
- value {
- bytes_list {
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- value: "\n\rAdam/beta_1:0\022\022Adam/beta_1/Assign\032!Adam/beta_1/Read/ReadVariableOp:0(\0012\'Adam/beta_1/Initializer/initial_value:08\001"
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- }
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- key: "variables"
- value {
- bytes_list {
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- }
- signature_def {
- key: "serving_default"
- value {
- inputs {
- key: "input_embedding_product_slug"
- value {
- name: "input_embedding_user_guid:0"
- dtype: DT_FLOAT
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- }
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- dtype: DT_FLOAT
- tensor_shape {
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- }
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- }
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- }
- outputs {
- key: "output"
- value {
- name: "sigmoid_out/Sigmoid:0"
- dtype: DT_FLOAT
- tensor_shape {
- dim {
- size: -1
- }
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- size: 1
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- }
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- }
- }
-}
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deleted file mode 100644
index 8339979323b..00000000000
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deleted file mode 100644
index 223ad4baf59..00000000000
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+++ /dev/null
Binary files differ
diff --git a/model-integration/src/test/models/tensorflow/external/modelv1/variables/variables.data-00000-of-00001 b/model-integration/src/test/models/tensorflow/external/modelv1/variables/variables.data-00000-of-00001
deleted file mode 100644
index 76e3a429612..00000000000
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index 285449d22c5..00000000000
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+++ /dev/null
Binary files differ
diff --git a/model-integration/src/test/models/tensorflow/external/modelv2/saved_model.pb b/model-integration/src/test/models/tensorflow/external/modelv2/saved_model.pb
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index e2af4d90552..00000000000
--- a/model-integration/src/test/models/tensorflow/external/modelv2/saved_model.pb
+++ /dev/null
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deleted file mode 100644
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+++ /dev/null
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diff --git a/model-integration/src/test/models/tensorflow/external/modelv2/variables/variables.index b/model-integration/src/test/models/tensorflow/external/modelv2/variables/variables.index
deleted file mode 100644
index 398e369c5e3..00000000000
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diff --git a/model-integration/src/test/models/tensorflow/external/train.py b/model-integration/src/test/models/tensorflow/external/train.py
deleted file mode 100644
index 32b14c481c3..00000000000
--- a/model-integration/src/test/models/tensorflow/external/train.py
+++ /dev/null
@@ -1,53 +0,0 @@
-# Copyright 2020 Oath Inc. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-import numpy as np
-import tensorflow as tf
-import tensorflow.keras.backend as K
-
-from tensorflow.keras.layers import Input, Dense, concatenate
-from tensorflow.keras.models import Model
-
-input_user = Input(shape=(3,))
-input_ad = Input(shape=(3,))
-
-merged = concatenate([input_user, input_ad])
-output_1 = Dense(64, activation='relu')(merged)
-output_2 = Dense(64, activation='relu')(output_1)
-predictions = Dense(1)(output_2)
-
-model = Model(inputs=[input_user, input_ad], outputs=predictions)
-model.compile(optimizer='adam',
- loss='binary_crossentropy',
- metrics=['accuracy'])
-model.summary()
-
-SAMPLES = 1000
-user_data = np.random.rand(SAMPLES,3)
-ad_data = np.random.rand(SAMPLES,3)
-labels = np.random.rand(SAMPLES,1)
-print(user_data[:10])
-print(ad_data[:10])
-print(labels[:10])
-
-model.fit([user_data, ad_data], labels, epochs=10, ) # starts training
-
-user_data_sample1 = np.random.rand(1, 3)
-ad_data_sample1 = np.random.rand(1, 3)
-
-print("predicting for:")
-print(user_data_sample1)
-print(ad_data_sample1)
-predictions = model.predict([user_data_sample1, ad_data_sample1])
-print(predictions)
-
-signature = tf.saved_model.signature_def_utils.predict_signature_def(
- inputs={'input1': model.inputs[0],'input2': model.inputs[1] }, outputs={'pctr': model.outputs[0]})
-
-builder = tf.saved_model.builder.SavedModelBuilder('modelv1')
-builder.add_meta_graph_and_variables(
- sess=K.get_session(),
- tags=[tf.saved_model.tag_constants.SERVING],
- signature_def_map={
- tf.saved_model.signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY:
- signature
- })
-builder.save()
diff --git a/model-integration/src/test/models/tensorflow/external/train_embed.py b/model-integration/src/test/models/tensorflow/external/train_embed.py
deleted file mode 100644
index 2d1ab18a0eb..00000000000
--- a/model-integration/src/test/models/tensorflow/external/train_embed.py
+++ /dev/null
@@ -1,66 +0,0 @@
-# Copyright 2020 Oath Inc. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
-import numpy as np
-import tensorflow as tf
-import tensorflow.keras.backend as K
-
-from tensorflow.keras.layers import Input, Dense, concatenate, Embedding, Reshape
-from tensorflow.keras.models import Model
-
-input_user = Input(shape=(3,))
-input_ad = Input(shape=(3,))
-gender_samples = Input(shape=(1,), dtype='int32')
-
-gender_values = ['m', 'f', 'a']
-
-gender_embeddings = Embedding(len(gender_values), 1)(gender_samples)
-reshape_gender = Reshape(target_shape=[1])(gender_embeddings)
-
-model2 = Model(inputs=[gender_samples], outputs=reshape_gender)
-model2.summary()
-
-merged = concatenate([input_user, input_ad, reshape_gender])
-output_1 = Dense(64, activation='relu')(merged)
-output_2 = Dense(64, activation='relu')(output_1)
-predictions = Dense(1)(output_2)
-
-model = Model(inputs=[input_user, input_ad, gender_samples], outputs=predictions)
-model.compile(optimizer='adam',
- loss='binary_crossentropy',
- metrics=['accuracy'])
-model.summary()
-
-SAMPLES = 1000
-user_data = np.random.rand(SAMPLES,3)
-ad_data = np.random.rand(SAMPLES,3)
-gender_data = np.random.randint(len(gender_values), size=SAMPLES)
-labels = np.random.rand(SAMPLES,1)
-print(user_data[:10])
-print(ad_data[:10])
-print(gender_data[:10])
-print(labels[:10])
-
-model.fit([user_data, ad_data, gender_data], labels, epochs=10, ) # starts training
-
-user_data_sample1 = np.random.rand(1, 3)
-ad_data_sample1 = np.random.rand(1, 3)
-gender_data_sample1 = np.random.randint(len(gender_values), size=1)
-
-print("predicting for:")
-print(user_data_sample1)
-print(ad_data_sample1)
-print(gender_data_sample1)
-predictions = model.predict([user_data_sample1, ad_data_sample1, gender_data_sample1])
-print(predictions)
-
-signature = tf.saved_model.signature_def_utils.predict_signature_def(
- inputs={'input1': model.inputs[0],'input2': model.inputs[1], 'input3': model.inputs[2] }, outputs={'pctrx': model.outputs[0]})
-
-builder = tf.saved_model.builder.SavedModelBuilder('modelv2')
-builder.add_meta_graph_and_variables(
- sess=K.get_session(),
- tags=[tf.saved_model.tag_constants.SERVING],
- signature_def_map={
- tf.saved_model.signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY:
- signature
- })
-builder.save()