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1/*
2Copyright 2016 The TensorFlow Authors. All Rights Reserved.
3
4Licensed under the Apache License, Version 2.0 (the "License");
5you may not use this file except in compliance with the License.
6You may obtain a copy of the License at
7
8    http://www.apache.org/licenses/LICENSE-2.0
9
10Unless required by applicable law or agreed to in writing, software
11distributed under the License is distributed on an "AS IS" BASIS,
12WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13See the License for the specific language governing permissions and
14limitations under the License.
15*/
16
17// Tests for the generated code of some operations.
18
19package op
20
21import (
22	"strings"
23	"testing"
24
25	tf "github.com/tensorflow/tensorflow/tensorflow/go"
26)
27
28func TestPlaceholder(t *testing.T) {
29	s := NewScope()
30	Placeholder(s.SubScope("x"), tf.Float, PlaceholderShape(tf.MakeShape(-1, 10)))
31	Placeholder(s.SubScope("y"), tf.Float, PlaceholderShape(tf.ScalarShape()))
32	Placeholder(s.SubScope("z"), tf.Float, PlaceholderShape(tf.Shape{}))
33	if _, err := s.Finalize(); err != nil {
34		t.Fatal(err)
35	}
36}
37
38func TestAddOperationFailure(t *testing.T) {
39	// Inspired from https://github.com/tensorflow/tensorflow/issues/9931
40	s := NewScope()
41
42	resize := ResizeArea(s, Placeholder(s, tf.Float), Const(s, []int64{80, 80}))
43	if err := s.Err(); err == nil {
44		t.Fatal("ResizeArea expects an int32 Tensor for size, should fail when an int64 is provided")
45	}
46	// And any use of resize should panic with an error message more informative than SIGSEGV
47	defer func() {
48		r := recover()
49		if r == nil {
50			return
51		}
52		s, ok := r.(string)
53		if ok && strings.Contains(s, "see Scope.Err() for details") {
54			return
55		}
56		t.Errorf("Expected panic string to Scope.Err(), found %T: %q", r, r)
57	}()
58	_ = resize.Shape()
59	t.Errorf("resize.Shape() should have paniced since the underlying Operation was not created")
60}
61
62func TestShapeAttribute(t *testing.T) {
63	s := NewScope()
64	x := Placeholder(s.SubScope("x"), tf.Int32, PlaceholderShape(tf.MakeShape(1)))
65	y := Placeholder(s.SubScope("y"), tf.Int32, PlaceholderShape(tf.Shape{}))
66	z := Add(s, x, y)
67	graph, err := s.Finalize()
68	if err != nil {
69		t.Fatal(err)
70	}
71	sess, err := tf.NewSession(graph, nil)
72	if err != nil {
73		t.Fatal(err)
74	}
75
76	value, err := tf.NewTensor([]int32{7})
77	if err != nil {
78		t.Fatal(err)
79	}
80	feeds := map[tf.Output]*tf.Tensor{
81		x: value,
82		y: value,
83	}
84	fetched, err := sess.Run(feeds, []tf.Output{z}, nil)
85	if err != nil {
86		t.Fatal(err)
87	}
88	if got, want := len(fetched), 1; got != want {
89		t.Fatalf("Fetched %d tensors, expected %d", got, want)
90	}
91	if got, want := fetched[0].Value().([]int32), []int32{14}; len(got) != len(want) || len(got) != 1 || got[0] != want[0] {
92		t.Fatalf("Got %v, want %v", got, want)
93	}
94}
95
96func TestDataset(t *testing.T) {
97	var (
98		s = NewScope()
99
100		// The use of a non-scalar here is inspired by
101		// https://github.com/tensorflow/tensorflow/issues/14891
102		c       = Const(s, []int32{21718, 31415})
103		types   = []tf.DataType{c.DataType()}
104		shapes  = []tf.Shape{c.Shape()}
105		dataset = TensorDataset(s, []tf.Output{c}, shapes)
106
107		iterator = Iterator(s, "", "", types, shapes)
108		next     = IteratorGetNext(s, iterator, types, shapes)
109		init     = MakeIterator(s, dataset, iterator)
110	)
111	graph, err := s.Finalize()
112	if err != nil {
113		t.Fatal(err)
114	}
115	sess, err := tf.NewSession(graph, nil)
116	if err != nil {
117		t.Fatal(err)
118	}
119	if _, err := sess.Run(nil, nil, []*tf.Operation{init}); err != nil {
120		t.Fatal(err)
121	}
122	results, err := sess.Run(nil, next, nil)
123	if err != nil {
124		t.Fatal(err)
125	}
126	got := results[0].Value().([]int32)
127	if len(got) != 2 || got[0] != 21718 || got[1] != 31415 {
128		t.Errorf("Got %v, want {21718, 31415}", got)
129	}
130	if _, err := sess.Run(nil, next, nil); err == nil {
131		t.Errorf("Expected sess.Run() to fail since the iterator should have reached the end of the dataset")
132	}
133}
134