Python tensorflow.tan() Examples
The following are 8
code examples of tensorflow.tan().
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: monopsr_output_builder.py From monopsr with MIT License | 6 votes |
def add_cen_x_output(self, output_key, pred_cen_z, pred_view_angs): output_type = self.output_config[output_key] print('\t{:30s}{}'.format(output_key, output_type)) with tf.variable_scope(output_key): if output_type == 'from_view_ang_and_z': # Predict centroid x using viewing angle cam2_pred_cen_x = pred_cen_z * tf.tan(pred_view_angs) # Adjust for x_offset cam_p = self.cam_p x_offset = -cam_p[0, 3] / cam_p[0, 0] pred_cen_x = cam2_pred_cen_x + x_offset else: raise ValueError('Invalid output_type', output_type) self._output_dict.add_unique_to_dict({ output_key: pred_cen_x, })
Example #2
Source File: test_forward.py From incubator-tvm with Apache License 2.0 | 6 votes |
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: ops.py From tfdeploy with MIT License | 5 votes |
def test_Tan(self): t = tf.tan(self.random(4, 3)) self.check(t)
Example #4
Source File: camera_utils.py From tf_mesh_renderer with Apache License 2.0 | 5 votes |
def perspective(aspect_ratio, fov_y, near_clip, far_clip): """Computes perspective transformation matrices. Functionality mimes gluPerspective (third_party/GL/glu/include/GLU/glu.h). Args: aspect_ratio: float value specifying the image aspect ratio (width/height). fov_y: 1-D float32 Tensor with shape [batch_size] specifying output vertical field of views in degrees. near_clip: 1-D float32 Tensor with shape [batch_size] specifying near clipping plane distance. far_clip: 1-D float32 Tensor with shape [batch_size] specifying far clipping plane distance. Returns: A [batch_size, 4, 4] float tensor that maps from right-handed points in eye space to left-handed points in clip space. """ # The multiplication of fov_y by pi/360.0 simultaneously converts to radians # and adds the half-angle factor of .5. focal_lengths_y = 1.0 / tf.tan(fov_y * (math.pi / 360.0)) depth_range = far_clip - near_clip p_22 = -(far_clip + near_clip) / depth_range p_23 = -2.0 * (far_clip * near_clip / depth_range) zeros = tf.zeros_like(p_23, dtype=tf.float32) # pyformat: disable perspective_transform = tf.concat( [ focal_lengths_y / aspect_ratio, zeros, zeros, zeros, zeros, focal_lengths_y, zeros, zeros, zeros, zeros, p_22, p_23, zeros, zeros, -tf.ones_like(p_23, dtype=tf.float32), zeros ], axis=0) # pyformat: enable perspective_transform = tf.reshape(perspective_transform, [4, 4, -1]) return tf.transpose(perspective_transform, [2, 0, 1])
Example #5
Source File: cwise_ops_test.py From deep_image_model with Apache License 2.0 | 5 votes |
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 |
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 |
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: test_forward.py From incubator-tvm with Apache License 2.0 | 5 votes |
def test_forward_atan2(): """test operator tan """ tf.disable_eager_execution() np_data_1 = np.random.uniform(1, 100, size=(2, 3, 5)).astype(np.float32) np_data_2 = np.random.uniform(1, 100, size=(2, 3, 5)).astype(np.float32) tf.reset_default_graph() in_data_1 = tf.placeholder(tf.float32, (2, 3, 5), name="in_data_1") in_data_2 = tf.placeholder(tf.float32, (2, 3, 5), name="in_data_2") tf.atan2(in_data_1, in_data_2, name="atan2") compare_tf_with_tvm([np_data_1, np_data_2], ['in_data_1:0', 'in_data_2:0'], 'atan2:0')