diff options
Diffstat (limited to 'src/armnnTfParser/test/FullyConnected.cpp')
| -rw-r--r-- | src/armnnTfParser/test/FullyConnected.cpp | 38 |
1 files changed, 19 insertions, 19 deletions
diff --git a/src/armnnTfParser/test/FullyConnected.cpp b/src/armnnTfParser/test/FullyConnected.cpp index 2a7b4951b7..e7f040e784 100644 --- a/src/armnnTfParser/test/FullyConnected.cpp +++ b/src/armnnTfParser/test/FullyConnected.cpp @@ -14,15 +14,15 @@ BOOST_AUTO_TEST_SUITE(TensorflowParser) // In Tensorflow fully connected layers are expressed as a MatMul followed by an Add. // The TfParser must detect this case and convert them to a FullyConnected layer. -struct FullyConnectedFixture : public ParserPrototxtFixture<armnnTfParser::ITfParser> +struct FullyConnectedFixture : public armnnUtils::ParserPrototxtFixture<armnnTfParser::ITfParser> { FullyConnectedFixture() { - // input = tf.placeholder(tf.float32, [1, 1], "input") - // weights = tf.constant([2], tf.float32, [1, 1]) - // matmul = tf.matmul(input, weights) - // bias = tf.constant([1], tf.float32) - // output = tf.add(matmul, bias, name="output") + // Input = tf.placeholder(tf.float32, [1, 1], "input") + // Weights = tf.constant([2], tf.float32, [1, 1]) + // Matmul = tf.matmul(input, weights) + // Bias = tf.constant([1], tf.float32) + // Output = tf.add(matmul, bias, name="output") m_Prototext = R"( node { name: "input" @@ -153,7 +153,7 @@ BOOST_FIXTURE_TEST_CASE(FullyConnected, FullyConnectedFixture) // C-- A A -- C // \ / // A -struct MatMulUsedInTwoFcFixture : public ParserPrototxtFixture<armnnTfParser::ITfParser> +struct MatMulUsedInTwoFcFixture : public armnnUtils::ParserPrototxtFixture<armnnTfParser::ITfParser> { MatMulUsedInTwoFcFixture() { @@ -326,7 +326,7 @@ BOOST_FIXTURE_TEST_CASE(MatMulUsedInTwoFc, MatMulUsedInTwoFcFixture) RunTest<1>({ 3 }, { 32 }); // Ideally we would check here that the armnn network has 5 layers: // Input, 2 x FullyConnected (biased), Add and Output. - // This would make sure the parser hasn't incorrectly added some unconnected layers corresponding to the MatMul + // This would make sure the parser hasn't incorrectly added some unconnected layers corresponding to the MatMul. } // Similar to MatMulUsedInTwoFc, but this time the Adds are 'staggered' (see diagram), which means that only one @@ -338,16 +338,16 @@ BOOST_FIXTURE_TEST_CASE(MatMulUsedInTwoFc, MatMulUsedInTwoFcFixture) // C2 -- A | // \ / // A -struct MatMulUsedInTwoFcStaggeredFixture : public ParserPrototxtFixture<armnnTfParser::ITfParser> +struct MatMulUsedInTwoFcStaggeredFixture : public armnnUtils::ParserPrototxtFixture<armnnTfParser::ITfParser> { MatMulUsedInTwoFcStaggeredFixture() { - // input = tf.placeholder(tf.float32, shape=[1,1], name = "input") - // const1 = tf.constant([17], tf.float32, [1,1]) - // mul = tf.matmul(input, const1) - // const2 = tf.constant([7], tf.float32, [1]) - // fc = tf.add(mul, const2) - // output = tf.add(mul, fc, name="output") + // Input = tf.placeholder(tf.float32, shape=[1,1], name = "input") + // Const1 = tf.constant([17], tf.float32, [1,1]) + // Mul = tf.matmul(input, const1) + // Monst2 = tf.constant([7], tf.float32, [1]) + // Fc = tf.add(mul, const2) + // Output = tf.add(mul, fc, name="output") m_Prototext = R"( node { name: "input" @@ -484,13 +484,13 @@ BOOST_FIXTURE_TEST_CASE(MatMulUsedInTwoFcStaggered, MatMulUsedInTwoFcStaggeredFi } // A MatMul in isolation, not connected to an add. Should result in a non-biased FullyConnected layer. -struct MatMulFixture : public ParserPrototxtFixture<armnnTfParser::ITfParser> +struct MatMulFixture : public armnnUtils::ParserPrototxtFixture<armnnTfParser::ITfParser> { MatMulFixture() { - // input = tf.placeholder(tf.float32, shape = [1, 1], name = "input") - // const = tf.constant([17], tf.float32, [1, 1]) - // output = tf.matmul(input, const, name = "output") + // Input = tf.placeholder(tf.float32, shape = [1, 1], name = "input") + // Const = tf.constant([17], tf.float32, [1, 1]) + // Output = tf.matmul(input, const, name = "output") m_Prototext = R"( node { name: "input" |