Python tensorflow.asin() Examples

The following are 9 code examples of tensorflow.asin(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module tensorflow , or try the search function .
Example #1
Source File: euler.py    From differentiable-point-clouds with MIT License 6 votes vote down vote up 
def ypr_from_campos(cx, cy, cz):
    camDist = math.sqrt(cx * cx + cy * cy + cz * cz)
    cx = cx / camDist
    cy = cy / camDist
    cz = cz / camDist
    t = math.sqrt(cx * cx + cy * cy)
    tx = cx / t
    ty = cy / t
    yaw = math.acos(tx)
    if ty > 0:
        yaw = 2 * math.pi - yaw

    roll = 0
    pitch = math.asin(cz)

    return yaw, pitch, roll
Example #2
Source File: test_forward.py    From incubator-tvm with Apache License 2.0 6 votes vote down vote up 
def test_forward_unary():
    def _test_forward_unary(op, a_min=1, a_max=5, dtype=np.float32):
        """test unary operators"""
        np_data = np.random.uniform(a_min, a_max, size=(2, 3, 5)).astype(dtype)
        tf.reset_default_graph()
        with tf.Graph().as_default():
            in_data = tf.placeholder(dtype, (2, 3, 5), name="in_data")
            out = op(in_data)
            compare_tf_with_tvm([np_data], ['in_data:0'], out.name)

    _test_forward_unary(tf.acos, -1, 1)
    _test_forward_unary(tf.asin, -1, 1)
    _test_forward_unary(tf.atanh, -1, 1)
    _test_forward_unary(tf.sinh)
    _test_forward_unary(tf.cosh)
    _test_forward_unary(tf.acosh)
    _test_forward_unary(tf.asinh)
    _test_forward_unary(tf.atan)
    _test_forward_unary(tf.sin)
    _test_forward_unary(tf.cos)
    _test_forward_unary(tf.tan)
    _test_forward_unary(tf.tanh)
    _test_forward_unary(tf.erf)
    _test_forward_unary(tf.log)
    _test_forward_unary(tf.log1p)
Example #3
Source File: uniform_distribution.py    From HyperGAN with MIT License 5 votes vote down vote up 
def periodic_triangle_waveform(z, p):
    return 2.0 / np.pi * tf.asin(tf.sin(2*np.pi*z/p))
Example #4
Source File: ops.py    From tfdeploy with MIT License 5 votes vote down vote up 
def test_Asin(self):
        t = tf.asin(self.random(4, 3))
        self.check(t)
Example #5
Source File: cwise_ops_test.py    From deep_image_model with Apache License 2.0 5 votes vote down vote up 
def testFloatBasic(self):
    x = np.arange(-3, 3).reshape(1, 3, 2).astype(np.float32)
    y = (x + .5).astype(np.float32)     # no zero
    z = (x + 15.5).astype(np.float32)   # all positive
    k = np.arange(-0.90, 0.90, 0.25).astype(np.float32) # between -1 and 1

    self._compareBoth(x, np.abs, tf.abs)
    self._compareBoth(x, np.abs, _ABS)
    self._compareBoth(x, np.negative, tf.neg)
    self._compareBoth(x, np.negative, _NEG)
    self._compareBoth(y, self._inv, tf.inv)
    self._compareBoth(x, np.square, tf.square)
    self._compareBoth(z, np.sqrt, tf.sqrt)
    self._compareBoth(z, self._rsqrt, tf.rsqrt)
    self._compareBoth(x, np.exp, tf.exp)
    self._compareBoth(z, np.log, tf.log)
    self._compareBoth(z, np.log1p, tf.log1p)
    self._compareBoth(x, np.tanh, tf.tanh)
    self._compareBoth(x, self._sigmoid, tf.sigmoid)
    self._compareBoth(y, np.sign, tf.sign)
    self._compareBoth(x, np.sin, tf.sin)
    self._compareBoth(x, np.cos, tf.cos)
    self._compareBoth(k, np.arcsin, tf.asin)
    self._compareBoth(k, np.arccos, tf.acos)
    self._compareBoth(x, np.arctan, tf.atan)
    self._compareBoth(x, np.tan, tf.tan)
    self._compareBoth(
        y,
        np.vectorize(self._replace_domain_error_with_inf(math.lgamma)),
        tf.lgamma)
    self._compareBoth(x, np.vectorize(math.erf), tf.erf)
    self._compareBoth(x, np.vectorize(math.erfc), tf.erfc)

    self._compareBothSparse(x, np.abs, tf.abs)
    self._compareBothSparse(x, np.negative, tf.neg)
    self._compareBothSparse(x, np.square, tf.square)
    self._compareBothSparse(z, np.sqrt, tf.sqrt, tol=1e-3)
    self._compareBothSparse(x, np.tanh, tf.tanh)
    self._compareBothSparse(y, np.sign, tf.sign)
    self._compareBothSparse(x, np.vectorize(math.erf), tf.erf)
Example #6
Source File: cwise_ops_test.py    From deep_image_model with Apache License 2.0 5 votes vote down vote up 
def testFloatEmpty(self):
    x = np.empty((2, 0, 5), dtype=np.float32)
    self._compareBoth(x, np.abs, tf.abs)
    self._compareBoth(x, np.abs, _ABS)
    self._compareBoth(x, np.negative, tf.neg)
    self._compareBoth(x, np.negative, _NEG)
    self._compareBoth(x, self._inv, tf.inv)
    self._compareBoth(x, np.square, tf.square)
    self._compareBoth(x, np.sqrt, tf.sqrt)
    self._compareBoth(x, self._rsqrt, tf.rsqrt)
    self._compareBoth(x, np.exp, tf.exp)
    self._compareBoth(x, np.log, tf.log)
    self._compareBoth(x, np.log1p, tf.log1p)
    self._compareBoth(x, np.tanh, tf.tanh)
    self._compareBoth(x, self._sigmoid, tf.sigmoid)
    self._compareBoth(x, np.sign, tf.sign)
    self._compareBoth(x, np.sin, tf.sin)
    self._compareBoth(x, np.cos, tf.cos)
    # Can't use vectorize below, so just use some arbitrary function
    self._compareBoth(x, np.sign, tf.lgamma)
    self._compareBoth(x, np.sign, tf.erf)
    self._compareBoth(x, np.sign, tf.erfc)
    self._compareBoth(x, np.tan, tf.tan)
    self._compareBoth(x, np.arcsin, tf.asin)
    self._compareBoth(x, np.arccos, tf.acos)
    self._compareBoth(x, np.arctan, tf.atan)

    self._compareBothSparse(x, np.abs, tf.abs)
    self._compareBothSparse(x, np.negative, tf.neg)
    self._compareBothSparse(x, np.square, tf.square)
    self._compareBothSparse(x, np.sqrt, tf.sqrt, tol=1e-3)
    self._compareBothSparse(x, np.tanh, tf.tanh)
    self._compareBothSparse(x, np.sign, tf.sign)
    self._compareBothSparse(x, np.sign, tf.erf)
Example #7
Source File: cwise_ops_test.py    From deep_image_model with Apache License 2.0 5 votes vote down vote up 
def testDoubleBasic(self):
    x = np.arange(-3, 3).reshape(1, 3, 2).astype(np.float64)
    y = (x + .5).astype(np.float64)    # no zero
    z = (x + 15.5).astype(np.float64)  # all positive
    k = np.arange(-0.90, 0.90, 0.35).reshape(1, 3, 2).astype(np.float64) # between -1 and 1
    self._compareBoth(x, np.abs, tf.abs)
    self._compareBoth(x, np.abs, _ABS)
    self._compareBoth(x, np.negative, tf.neg)
    self._compareBoth(x, np.negative, _NEG)
    self._compareBoth(y, self._inv, tf.inv)
    self._compareBoth(x, np.square, tf.square)
    self._compareBoth(z, np.sqrt, tf.sqrt)
    self._compareBoth(z, self._rsqrt, tf.rsqrt)
    self._compareBoth(x, np.exp, tf.exp)
    self._compareBoth(z, np.log, tf.log)
    self._compareBoth(z, np.log1p, tf.log1p)
    self._compareBoth(x, np.tanh, tf.tanh)
    self._compareBoth(x, self._sigmoid, tf.sigmoid)
    self._compareBoth(y, np.sign, tf.sign)
    self._compareBoth(x, np.sin, tf.sin)
    self._compareBoth(x, np.cos, tf.cos)
    self._compareBoth(
        y,
        np.vectorize(self._replace_domain_error_with_inf(math.lgamma)),
        tf.lgamma)
    self._compareBoth(x, np.vectorize(math.erf), tf.erf)
    self._compareBoth(x, np.vectorize(math.erfc), tf.erfc)
    self._compareBoth(x, np.arctan, tf.atan)
    self._compareBoth(k, np.arcsin, tf.asin)
    self._compareBoth(k, np.arccos, tf.acos)
    self._compareBoth(k, np.tan, tf.tan)

    self._compareBothSparse(x, np.abs, tf.abs)
    self._compareBothSparse(x, np.negative, tf.neg)
    self._compareBothSparse(x, np.square, tf.square)
    self._compareBothSparse(z, np.sqrt, tf.sqrt, tol=1e-3)
    self._compareBothSparse(x, np.tanh, tf.tanh)
    self._compareBothSparse(y, np.sign, tf.sign)
    self._compareBothSparse(x, np.vectorize(math.erf), tf.erf)
Example #8
Source File: ModelNet40.py    From KPConv with MIT License 4 votes vote down vote up 
def get_tf_mapping(self, config):

        def tf_map(stacked_points, stacked_normals, labels, obj_inds, stack_lengths):
            """
            From the input point cloud, this function compute all the point clouds at each layer, the neighbors
            indices, the pooling indices and other useful variables.
            :param stacked_points: Tensor with size [None, 3] where None is the total number of points
            :param labels: Tensor with size [None] where None is the number of batch
            :param stack_lengths: Tensor with size [None] where None is the number of batch
            """

            # Get batch indice for each point
            batch_inds = self.tf_get_batch_inds(stack_lengths)

            # Augment input points
            stacked_points, scales, rots = self.tf_augment_input(stacked_points,
                                                                 batch_inds,
                                                                 config)

            # First add a column of 1 as feature for the network to be able to learn 3D shapes
            stacked_features = tf.ones((tf.shape(stacked_points)[0], 1), dtype=tf.float32)

            # Then use positions or not
            if config.in_features_dim == 1:
                pass
            elif config.in_features_dim == 3:
                stacked_features = tf.concat((stacked_features, stacked_points), axis=1)
            elif config.in_features_dim == 4:
                stacked_features = tf.concat((stacked_features, stacked_normals), axis=1)
            elif config.in_features_dim == 5:
                angles = tf.asin(tf.abs(stacked_normals)) * (2 / np.pi)
                stacked_features = tf.concat((stacked_features, angles), axis=1)
            elif config.in_features_dim == 7:
                stacked_features = tf.concat((stacked_features, stacked_points, stacked_normals), axis=1)
            else:
                raise ValueError('Only accepted input dimensions are 1, 4 and 7 (without and with XYZ)')

            # Get the whole input list
            input_list = self.tf_classification_inputs(config,
                                                       stacked_points,
                                                       stacked_features,
                                                       labels,
                                                       stack_lengths,
                                                       batch_inds)

            # Add scale and rotation for testing
            input_list += [scales, rots, obj_inds]

            return input_list

        return tf_map

    # Debug methods
    # ------------------------------------------------------------------------------------------------------------------
Example #9
Source File: euler.py    From differentiable-point-clouds with MIT License 4 votes vote down vote up 
def quaternion2euler_full_tf(q, rotseq="yzy"):
    def twoaxisrot_tf(r11, r12, r21, r31, r32):
        a0 = tf.atan2(r11, r12)
        a1 = tf.acos(r21)
        a2 = tf.atan2(r31, r32)
        return tf.stack([a0, a1, a2], axis=-1)

    def threeaxisrot_tf(r11, r12, r21, r31, r32):
        a0 = tf.atan2(r31, r32)
        a1 = tf.asin(tf.clip_by_value(r21, -1.0, 1.0))
        a2 = tf.atan2(r11, r12)
        return tf.stack([a0, a1, a2], axis=-1)

    q_norm = tf.expand_dims(tf.norm(q, axis=-1), axis=-1)
    q /= q_norm

    if rotseq == "yzy":
        angles = twoaxisrot_tf(2 * (q[:, 2] * q[:, 3] + q[:, 0] * q[:, 1]),
                               -2 * (q[:, 1] * q[:, 2] - q[:, 0] * q[:, 3]),
                               q[:, 0] * q[:, 0] - q[:, 1] * q[:, 1] + q[:, 2] * q[:, 2] - q[:, 3] * q[:, 3],
                               2 * (q[:, 2] * q[:, 3] - q[:, 0] * q[:, 1]),
                               2 * (q[:, 1] * q[:, 2] + q[:, 0] * q[:, 3]))
        yaw = angles[:, 2]
        pitch = angles[:, 1]
    elif rotseq == "xzy":
        angles = threeaxisrot_tf(2 * (q[:, 2] * q[:, 3] + q[:, 0] * q[:, 1]),
                                 q[:, 0] * q[:, 0] - q[:, 1] * q[:, 1] + q[:, 2] * q[:, 2] - q[:, 3] * q[:, 3],
                                 -2 * (q[:, 1] * q[:, 2] - q[:, 0] * q[:, 3]),
                                 2 * (q[:, 1] * q[:, 3] + q[:, 0] * q[:, 2]),
                                 q[:, 0] * q[:, 0] + q[:, 1] * q[:, 1] - q[:, 2] * q[:, 2] - q[:, 3] * q[:, 3])
        yaw = angles[:, 0]
        pitch = angles[:, 1]
    elif rotseq == "zxy":
        angles = threeaxisrot_tf(-2 * (q[:, 1] * q[:, 2] - q[:, 0] * q[:, 3]),
                                 q[:, 0] * q[:, 0] - q[:, 1] * q[:, 1] + q[:, 2] * q[:, 2] - q[:, 3] * q[:, 3],
                                 2 * (q[:, 2] * q[:, 3] + q[:, 0] * q[:, 1]),
                                 -2 * (q[:, 1] * q[:, 3] - q[:, 0] * q[:, 2]),
                                 q[:, 0] * q[:, 0] - q[:, 1] * q[:, 1] - q[:, 2] * q[:, 2] + q[:, 3] * q[:, 3])
        yaw = angles[:, 0]
        pitch = angles[:, 2]

    return yaw, pitch