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Commit 957ee975 authored by Mark Daoust's avatar Mark Daoust
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Resolve review comments - part 1

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samples/core/tutorials/estimators/wide.ipynb
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...@@ -356,14 +356,12 @@ ...@@ -356,14 +356,12 @@
"source": [ "source": [
"ds = easy_input_function(train_df, label_key='income_bracket', num_epochs=5, shuffle=True, batch_size=10)\n", "ds = easy_input_function(train_df, label_key='income_bracket', num_epochs=5, shuffle=True, batch_size=10)\n",
"\n", "\n",
"for feature_batch, label_batch in ds:\n", "for feature_batch, label_batch in ds.take(1):\n",
" break\n", " print('Some feature keys:', list(feature_batch.keys())[:5])\n",
" \n", " print()\n",
"print('Some feature keys:', list(feature_batch.keys())[:5])\n", " print('A batch of Ages :', feature_batch['age'])\n",
"print()\n", " print()\n",
"print('A batch of Ages :', feature_batch['age'])\n", " print('A batch of Labels:', label_batch )"
"print()\n",
"print('A batch of Labels:', label_batch )"
], ],
"execution_count": 0, "execution_count": 0,
"outputs": [] "outputs": []
...@@ -426,14 +424,12 @@ ...@@ -426,14 +424,12 @@
}, },
"cell_type": "code", "cell_type": "code",
"source": [ "source": [
"for feature_batch, label_batch in ds:\n", "for feature_batch, label_batch in ds.take(1):\n",
" break\n", " print('Feature keys:', list(feature_batch.keys())[:5])\n",
" \n", " print()\n",
"print('Feature keys:', list(feature_batch.keys())[:5])\n", " print('Age batch :', feature_batch['age'])\n",
"print()\n", " print()\n",
"print('Age batch :', feature_batch['age'])\n", " print('Label batch :', label_batch )"
"print()\n",
"print('Label batch :', label_batch )"
], ],
"execution_count": 0, "execution_count": 0,
"outputs": [] "outputs": []
...@@ -546,7 +542,7 @@ ...@@ -546,7 +542,7 @@
}, },
"cell_type": "code", "cell_type": "code",
"source": [ "source": [
"classifier = tf.estimator.LinearClassifier(feature_columns=[age], n_classes=2)\n", "classifier = tf.estimator.LinearClassifier(feature_columns=[age])\n",
"classifier.train(train_inpf)\n", "classifier.train(train_inpf)\n",
"result = classifier.evaluate(test_inpf)\n", "result = classifier.evaluate(test_inpf)\n",
"\n", "\n",
...@@ -627,7 +623,7 @@ ...@@ -627,7 +623,7 @@
}, },
"cell_type": "code", "cell_type": "code",
"source": [ "source": [
"classifier = tf.estimator.LinearClassifier(feature_columns=my_numeric_columns, n_classes=2)\n", "classifier = tf.estimator.LinearClassifier(feature_columns=my_numeric_columns)\n",
"classifier.train(train_inpf)\n", "classifier.train(train_inpf)\n",
"\n", "\n",
"result = classifier.evaluate(test_inpf)\n", "result = classifier.evaluate(test_inpf)\n",
...@@ -876,7 +872,7 @@ ...@@ -876,7 +872,7 @@
}, },
"cell_type": "code", "cell_type": "code",
"source": [ "source": [
"classifier = tf.estimator.LinearClassifier(feature_columns=my_numeric_columns+my_categorical_columns, n_classes=2)\n", "classifier = tf.estimator.LinearClassifier(feature_columns=my_numeric_columns+my_categorical_columns)\n",
"classifier.train(train_inpf)\n", "classifier.train(train_inpf)\n",
"result = classifier.evaluate(test_inpf)\n", "result = classifier.evaluate(test_inpf)\n",
"\n", "\n",
......
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