test_class.file: deepnetts-core/src/test/java/deepnetts/net/layers/ActivationFunctionsTest.java
test_class.identifier: ActivationFunctionsTest
test_case.body: @Test
      public void testTanhPrime() {
          float[] x = {-0.999998f,  -0.999998f,  -0.999997f,  -0.999997f,  -0.999996f,  -0.999995f,  -0.999994f,  -0.999993f,  -0.999992f,  -0.99999f,  -0.999988f,  -0.999985f,  -0.999982f,  -0.999978f,  -0.999973f,  -0.999967f,  -0.999959f,  -0.99995f,  -0.999939f,  -0.999926f,  -0.999909f,  -0.999889f,  -0.999865f,  -0.999835f,  -0.999798f,  -0.999753f,  -0.999699f,  -0.999632f,  -0.99955f,  -0.999451f,  -0.999329f,  -0.999181f,  -0.999f,  -0.998778f,  -0.998508f,  -0.998178f,  -0.997775f,  -0.997283f,  -0.996682f,  -0.995949f,  -0.995055f,  -0.993963f,  -0.992631f,  -0.991007f,  -0.989027f,  -0.986614f,  -0.983675f,  -0.980096f,  -0.975743f,  -0.970452f,  -0.964028f,  -0.956237f,  -0.946806f,  -0.935409f,  -0.921669f,  -0.905148f,  -0.885352f,  -0.861723f,  -0.833655f,  -0.800499f,  -0.761594f,  -0.716298f,  -0.664037f,  -0.604368f,  -0.53705f,  -0.462117f,  -0.379949f,  -0.291313f,  -0.197375f,  -0.099668f,  -2.4869e-14f,  0.099668f,  0.197375f,  0.291313f,  0.379949f,  0.462117f,  0.53705f,  0.604368f,  0.664037f,  0.716298f,  0.761594f,  0.800499f,  0.833655f,  0.861723f,  0.885352f,  0.905148f,  0.921669f,  0.935409f,  0.946806f,  0.956237f,  0.964028f,  0.970452f,  0.975743f,  0.980096f,  0.983675f,  0.986614f,  0.989027f,  0.991007f,  0.992631f,  0.993963f,  0.995055f,  0.995949f,  0.996682f,  0.997283f,  0.997775f,  0.998178f,  0.998508f,  0.998778f,  0.999f,  0.999181f,  0.999329f,  0.999451f,  0.99955f,  0.999632f,  0.999699f,  0.999753f,  0.999798f,  0.999835f,  0.999865f,  0.999889f,  0.999909f,  0.999926f,  0.999939f,  0.99995f,  0.999959f,  0.999967f,  0.999973f,  0.999978f,  0.999982f,  0.999985f,  0.999988f,  0.99999f,  0.999992f,  0.999993f,  0.999994f,  0.999995f,  0.999996f,  0.999997f,  0.999997f,  0.999998f,  0.999998f};
          float[] y = {3.32611e-06f,  4.06252e-06f,  4.96197e-06f,  6.06056e-06f,  7.40238e-06f,  9.04128e-06f,  1.1043e-05f,  1.3488e-05f,  1.64742e-05f,  2.01216e-05f,  2.45765e-05f,  3.00178e-05f,  3.66637e-05f,  4.47809e-05f,  5.46953e-05f,  6.68046e-05f,  8.15947e-05f,  9.96591e-05f,  0.000121723f,  0.00014867f,  0.000181583f,  0.000221782f,  0.000270878f,  0.000330842f,  0.000404076f,  0.000493517f,  0.000602751f,  0.000736152f,  0.000899065f,  0.00109801f,  0.00134095f,  0.0016376f,  0.0019998f,  0.00244202f,  0.00298189f,  0.00364088f,  0.00444519f,  0.0054267f,  0.0066242f,  0.00808487f,  0.00986604f,  0.0120372f,  0.0146827f,  0.0179042f,  0.0218248f,  0.0265922f,  0.0323838f,  0.0394111f,  0.0479253f,  0.058223f,  0.0706508f,  0.0856099f,  0.103558f,  0.12501f,  0.150527f,  0.180707f,  0.216152f,  0.257433f,  0.30502f,  0.359201f,  0.419974f,  0.486917f,  0.559055f,  0.63474f,  0.711578f,  0.786448f,  0.855639f,  0.915137f,  0.961043f,  0.990066f,  1.0f,  0.990066f,  0.961043f,  0.915137f,  0.855639f,  0.786448f,  0.711578f,  0.63474f,  0.559055f,  0.486917f,  0.419974f,  0.359201f,  0.30502f,  0.257433f,  0.216152f,  0.180707f,  0.150527f,  0.12501f,  0.103558f,  0.0856099f,  0.0706508f,  0.058223f,  0.0479253f,  0.0394111f,  0.0323838f,  0.0265922f,  0.0218248f,  0.0179042f,  0.0146827f,  0.0120372f,  0.00986604f,  0.00808487f,  0.0066242f,  0.0054267f,  0.00444519f,  0.00364088f,  0.00298189f,  0.00244202f,  0.0019998f,  0.0016376f,  0.00134095f,  0.00109801f,  0.000899065f,  0.000736152f,  0.000602751f,  0.000493517f,  0.000404076f,  0.000330842f,  0.000270878f,  0.000221782f,  0.000181583f,  0.00014867f,  0.000121723f,  9.96591e-05f,  8.15947e-05f,  6.68046e-05f,  5.46953e-05f,  4.47809e-05f,  3.66637e-05f,  3.00178e-05f,  2.45765e-05f,  2.01216e-05f,  1.64742e-05f,  1.3488e-05f,  1.1043e-05f,  9.04128e-06f,  7.40238e-06f,  6.06056e-06f,  4.96197e-06f,  4.06252e-06f,  3.32611e-06f};
                 
          for (int i = 0; i < x.length; i++) {
              float expResult = y[i];
              float result = ActivationFunctions.tanhPrime(x[i]);
              assertEquals(expResult, result, 1e-6);
          }  
      }
test_case.class_method_signature: ActivationFunctionsTest.testTanhPrime()
test_case.full_signature: @Test public void testTanhPrime()
test_case.identifier: testTanhPrime
test_case.invocations: tanhPrime assertEquals
test_case.modifiers: @Test public
test_case.parameters: ()
test_case.return: void
test_case.signature: void testTanhPrime()
focal_class.file: deepnetts-core/src/main/java/deepnetts/net/layers/ActivationFunctions.java
focal_class.identifier: ActivationFunctions
focal_class.class_method_signature: ActivationFunctions.ActivationFunctions()
focal_class.full_signature: private  ActivationFunctions()
focal_class.identifier: ActivationFunctions
focal_class.modifiers: private
focal_class.parameters: ()
focal_class.signature:  ActivationFunctions()
focal_class.class_method_signature: ActivationFunctions.calc(final ActivationType type, final float x)
focal_class.full_signature: public static final float calc(final ActivationType type, final float x)
focal_class.identifier: calc
focal_class.modifiers: public static final
focal_class.parameters: (final ActivationType type, final float x)
focal_class.return: float
focal_class.signature: float calc(final ActivationType type, final float x)
focal_class.class_method_signature: ActivationFunctions.prime(ActivationType type, float y)
focal_class.full_signature: public static final float prime(ActivationType type, float y)
focal_class.identifier: prime
focal_class.modifiers: public static final
focal_class.parameters: (ActivationType type, float y)
focal_class.return: float
focal_class.signature: float prime(ActivationType type, float y)
focal_class.class_method_signature: ActivationFunctions.sigmoid(final float x)
focal_class.full_signature: public static final float sigmoid(final float x)
focal_class.identifier: sigmoid
focal_class.modifiers: public static final
focal_class.parameters: (final float x)
focal_class.return: float
focal_class.signature: float sigmoid(final float x)
focal_class.class_method_signature: ActivationFunctions.sigmoidPrime(final float y)
focal_class.full_signature: public static final float sigmoidPrime(final float y)
focal_class.identifier: sigmoidPrime
focal_class.modifiers: public static final
focal_class.parameters: (final float y)
focal_class.return: float
focal_class.signature: float sigmoidPrime(final float y)
focal_class.class_method_signature: ActivationFunctions.tanh(final float x)
focal_class.full_signature: public static final float tanh(final float x)
focal_class.identifier: tanh
focal_class.modifiers: public static final
focal_class.parameters: (final float x)
focal_class.return: float
focal_class.signature: float tanh(final float x)
focal_class.class_method_signature: ActivationFunctions.tanhPrime(final float y)
focal_class.full_signature: public static final float tanhPrime(final float y)
focal_class.identifier: tanhPrime
focal_class.modifiers: public static final
focal_class.parameters: (final float y)
focal_class.return: float
focal_class.signature: float tanhPrime(final float y)
focal_class.class_method_signature: ActivationFunctions.relu(final float x)
focal_class.full_signature: public static final float relu(final float x)
focal_class.identifier: relu
focal_class.modifiers: public static final
focal_class.parameters: (final float x)
focal_class.return: float
focal_class.signature: float relu(final float x)
focal_class.class_method_signature: ActivationFunctions.reluPrime(final float y)
focal_class.full_signature: public static final float reluPrime(final float y)
focal_class.identifier: reluPrime
focal_class.modifiers: public static final
focal_class.parameters: (final float y)
focal_class.return: float
focal_class.signature: float reluPrime(final float y)
focal_class.class_method_signature: ActivationFunctions.linear(final float x)
focal_class.full_signature: public static final float linear(final float x)
focal_class.identifier: linear
focal_class.modifiers: public static final
focal_class.parameters: (final float x)
focal_class.return: float
focal_class.signature: float linear(final float x)
focal_class.class_method_signature: ActivationFunctions.linearPrime(final float y)
focal_class.full_signature: public static final float linearPrime(final float y)
focal_class.identifier: linearPrime
focal_class.modifiers: public static final
focal_class.parameters: (final float y)
focal_class.return: float
focal_class.signature: float linearPrime(final float y)
focal_method.body: public static final float tanhPrime(final float y) {     
          return (1-y*y);
      }
focal_method.class_method_signature: ActivationFunctions.tanhPrime(final float y)
focal_method.full_signature: public static final float tanhPrime(final float y)
focal_method.identifier: tanhPrime
focal_method.modifiers: public static final
focal_method.parameters: (final float y)
focal_method.return: float
focal_method.signature: float tanhPrime(final float y)