Python numpy.right_shift() Examples
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Example #1
Source File: test_ufunc.py From GraphicDesignPatternByPython with MIT License | 6 votes |
def test_NotImplemented_not_returned(self): # See gh-5964 and gh-2091. Some of these functions are not operator # related and were fixed for other reasons in the past. binary_funcs = [ np.power, np.add, np.subtract, np.multiply, np.divide, np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or, np.bitwise_xor, np.left_shift, np.right_shift, np.fmax, np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2, np.logical_and, np.logical_or, np.logical_xor, np.maximum, np.minimum, np.mod ] # These functions still return NotImplemented. Will be fixed in # future. # bad = [np.greater, np.greater_equal, np.less, np.less_equal, np.not_equal] a = np.array('1') b = 1 for f in binary_funcs: assert_raises(TypeError, f, a, b)
Example #2
Source File: modis_l2.py From satpy with GNU General Public License v3.0 | 6 votes |
def bits_strip(bit_start, bit_count, value): """Extract specified bit from bit representation of integer value. Parameters ---------- bit_start : int Starting index of the bits to extract (first bit has index 0) bit_count : int Number of bits starting from bit_start to extract value : int Number from which to extract the bits Returns ------- int Value of the extracted bits """ bit_mask = pow(2, bit_start + bit_count) - 1 return np.right_shift(np.bitwise_and(value, bit_mask), bit_start)
Example #3
Source File: test_ufunc.py From elasticintel with GNU General Public License v3.0 | 6 votes |
def test_NotImplemented_not_returned(self): # See gh-5964 and gh-2091. Some of these functions are not operator # related and were fixed for other reasons in the past. binary_funcs = [ np.power, np.add, np.subtract, np.multiply, np.divide, np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or, np.bitwise_xor, np.left_shift, np.right_shift, np.fmax, np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2, np.logical_and, np.logical_or, np.logical_xor, np.maximum, np.minimum, np.mod ] # These functions still return NotImplemented. Will be fixed in # future. # bad = [np.greater, np.greater_equal, np.less, np.less_equal, np.not_equal] a = np.array('1') b = 1 for f in binary_funcs: assert_raises(TypeError, f, a, b)
Example #4
Source File: test_Sim.py From basil with BSD 3-Clause "New" or "Revised" License | 6 votes |
def test_simple(self): input_arr = bitarray('10' * 64) self.chip['PIXEL_REG'][:] = input_arr self.chip['PIXEL_REG'][0] = 0 self.chip.program_pixel_reg() ret = self.chip['DATA'].get_data() data0 = ret.astype(np.uint8) data1 = np.right_shift(ret, 8).astype(np.uint8) data = np.reshape(np.vstack((data1, data0)), -1, order='F') bdata = np.unpackbits(data) input_arr[0] = 0 self.assertEqual(input_arr.tolist(), bdata.tolist())
Example #5
Source File: LCD_1in44.py From Piano-LED-Visualizer with MIT License | 6 votes |
def LCD_ShowImage(self,Image,Xstart,Ystart): if (Image == None): return imwidth, imheight = Image.size if imwidth != self.width or imheight != self.height: raise ValueError('Image must be same dimensions as display \ ({0}x{1}).' .format(self.width, self.height)) img = np.asarray(Image) pix = np.zeros((self.width,self.height,2), dtype = np.uint8) pix[...,[0]] = np.add(np.bitwise_and(img[...,[0]],0xF8),np.right_shift(img[...,[1]],5)) pix[...,[1]] = np.add(np.bitwise_and(np.left_shift(img[...,[1]],3),0xE0),np.right_shift(img[...,[2]],3)) pix = pix.flatten().tolist() self.LCD_SetWindows(0, 0, self.width , self.height) GPIO.output(LCD_Config.LCD_DC_PIN, GPIO.HIGH) for i in range(0,len(pix),4096): LCD_Config.SPI_Write_Byte(pix[i:i+4096])
Example #6
Source File: test_ufunc.py From coffeegrindsize with MIT License | 6 votes |
def test_NotImplemented_not_returned(self): # See gh-5964 and gh-2091. Some of these functions are not operator # related and were fixed for other reasons in the past. binary_funcs = [ np.power, np.add, np.subtract, np.multiply, np.divide, np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or, np.bitwise_xor, np.left_shift, np.right_shift, np.fmax, np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2, np.logical_and, np.logical_or, np.logical_xor, np.maximum, np.minimum, np.mod, np.greater, np.greater_equal, np.less, np.less_equal, np.equal, np.not_equal] a = np.array('1') b = 1 c = np.array([1., 2.]) for f in binary_funcs: assert_raises(TypeError, f, a, b) assert_raises(TypeError, f, c, a)
Example #7
Source File: test_ufunc.py From mxnet-lambda with Apache License 2.0 | 6 votes |
def test_NotImplemented_not_returned(self): # See gh-5964 and gh-2091. Some of these functions are not operator # related and were fixed for other reasons in the past. binary_funcs = [ np.power, np.add, np.subtract, np.multiply, np.divide, np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or, np.bitwise_xor, np.left_shift, np.right_shift, np.fmax, np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2, np.logical_and, np.logical_or, np.logical_xor, np.maximum, np.minimum, np.mod ] # These functions still return NotImplemented. Will be fixed in # future. # bad = [np.greater, np.greater_equal, np.less, np.less_equal, np.not_equal] a = np.array('1') b = 1 for f in binary_funcs: assert_raises(TypeError, f, a, b)
Example #8
Source File: test_ufunc.py From pySINDy with MIT License | 6 votes |
def test_NotImplemented_not_returned(self): # See gh-5964 and gh-2091. Some of these functions are not operator # related and were fixed for other reasons in the past. binary_funcs = [ np.power, np.add, np.subtract, np.multiply, np.divide, np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or, np.bitwise_xor, np.left_shift, np.right_shift, np.fmax, np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2, np.logical_and, np.logical_or, np.logical_xor, np.maximum, np.minimum, np.mod ] # These functions still return NotImplemented. Will be fixed in # future. # bad = [np.greater, np.greater_equal, np.less, np.less_equal, np.not_equal] a = np.array('1') b = 1 for f in binary_funcs: assert_raises(TypeError, f, a, b)
Example #9
Source File: test_ufunc.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
def test_NotImplemented_not_returned(self): # See gh-5964 and gh-2091. Some of these functions are not operator # related and were fixed for other reasons in the past. binary_funcs = [ np.power, np.add, np.subtract, np.multiply, np.divide, np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or, np.bitwise_xor, np.left_shift, np.right_shift, np.fmax, np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2, np.logical_and, np.logical_or, np.logical_xor, np.maximum, np.minimum, np.mod, np.greater, np.greater_equal, np.less, np.less_equal, np.equal, np.not_equal] a = np.array('1') b = 1 c = np.array([1., 2.]) for f in binary_funcs: assert_raises(TypeError, f, a, b) assert_raises(TypeError, f, c, a)
Example #10
Source File: test_op_level4.py From incubator-tvm with Apache License 2.0 | 6 votes |
def test_binary_int_broadcast_1(): for op, ref in [(relay.right_shift, np.right_shift), (relay.left_shift, np.left_shift)]: x = relay.var("x", relay.TensorType((10, 4), "int32")) y = relay.var("y", relay.TensorType((5, 10, 1), "int32")) z = op(x, y) zz = run_infer_type(z) assert zz.checked_type == relay.TensorType((5, 10, 4), "int32") if ref is not None: x_shape = (10, 4) y_shape = (5, 10, 1) t1 = relay.TensorType(x_shape, 'int32') t2 = relay.TensorType(y_shape, 'int32') x_data = np.random.randint(1, 10000, size=(x_shape)).astype(t1.dtype) y_data = np.random.randint(1, 31, size=(y_shape)).astype(t2.dtype) func = relay.Function([x, y], z) ref_res = ref(x_data, y_data) for target, ctx in ctx_list(): intrp = relay.create_executor("graph", ctx=ctx, target=target) op_res = intrp.evaluate(func)(x_data, y_data) tvm.testing.assert_allclose(op_res.asnumpy(), ref_res)
Example #11
Source File: test_ufunc.py From Mastering-Elasticsearch-7.0 with MIT License | 6 votes |
def test_NotImplemented_not_returned(self): # See gh-5964 and gh-2091. Some of these functions are not operator # related and were fixed for other reasons in the past. binary_funcs = [ np.power, np.add, np.subtract, np.multiply, np.divide, np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or, np.bitwise_xor, np.left_shift, np.right_shift, np.fmax, np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2, np.logical_and, np.logical_or, np.logical_xor, np.maximum, np.minimum, np.mod, np.greater, np.greater_equal, np.less, np.less_equal, np.equal, np.not_equal] a = np.array('1') b = 1 c = np.array([1., 2.]) for f in binary_funcs: assert_raises(TypeError, f, a, b) assert_raises(TypeError, f, c, a)
Example #12
Source File: test_ufunc.py From vnpy_crypto with MIT License | 6 votes |
def test_NotImplemented_not_returned(self): # See gh-5964 and gh-2091. Some of these functions are not operator # related and were fixed for other reasons in the past. binary_funcs = [ np.power, np.add, np.subtract, np.multiply, np.divide, np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or, np.bitwise_xor, np.left_shift, np.right_shift, np.fmax, np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2, np.logical_and, np.logical_or, np.logical_xor, np.maximum, np.minimum, np.mod ] # These functions still return NotImplemented. Will be fixed in # future. # bad = [np.greater, np.greater_equal, np.less, np.less_equal, np.not_equal] a = np.array('1') b = 1 for f in binary_funcs: assert_raises(TypeError, f, a, b)
Example #13
Source File: test_ufunc.py From auto-alt-text-lambda-api with MIT License | 6 votes |
def test_NotImplemented_not_returned(self): # See gh-5964 and gh-2091. Some of these functions are not operator # related and were fixed for other reasons in the past. binary_funcs = [ np.power, np.add, np.subtract, np.multiply, np.divide, np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or, np.bitwise_xor, np.left_shift, np.right_shift, np.fmax, np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2, np.logical_and, np.logical_or, np.logical_xor, np.maximum, np.minimum, np.mod ] # These functions still return NotImplemented. Will be fixed in # future. # bad = [np.greater, np.greater_equal, np.less, np.less_equal, np.not_equal] a = np.array('1') b = 1 for f in binary_funcs: assert_raises(TypeError, f, a, b)
Example #14
Source File: test_ufunc.py From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License | 6 votes |
def test_NotImplemented_not_returned(self): # See gh-5964 and gh-2091. Some of these functions are not operator # related and were fixed for other reasons in the past. binary_funcs = [ np.power, np.add, np.subtract, np.multiply, np.divide, np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or, np.bitwise_xor, np.left_shift, np.right_shift, np.fmax, np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2, np.logical_and, np.logical_or, np.logical_xor, np.maximum, np.minimum, np.mod ] # These functions still return NotImplemented. Will be fixed in # future. # bad = [np.greater, np.greater_equal, np.less, np.less_equal, np.not_equal] a = np.array('1') b = 1 for f in binary_funcs: assert_raises(TypeError, f, a, b)
Example #15
Source File: test_ufunc.py From twitter-stock-recommendation with MIT License | 6 votes |
def test_NotImplemented_not_returned(self): # See gh-5964 and gh-2091. Some of these functions are not operator # related and were fixed for other reasons in the past. binary_funcs = [ np.power, np.add, np.subtract, np.multiply, np.divide, np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or, np.bitwise_xor, np.left_shift, np.right_shift, np.fmax, np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2, np.logical_and, np.logical_or, np.logical_xor, np.maximum, np.minimum, np.mod ] # These functions still return NotImplemented. Will be fixed in # future. # bad = [np.greater, np.greater_equal, np.less, np.less_equal, np.not_equal] a = np.array('1') b = 1 for f in binary_funcs: assert_raises(TypeError, f, a, b)
Example #16
Source File: test_ufunc.py From keras-lambda with MIT License | 6 votes |
def test_NotImplemented_not_returned(self): # See gh-5964 and gh-2091. Some of these functions are not operator # related and were fixed for other reasons in the past. binary_funcs = [ np.power, np.add, np.subtract, np.multiply, np.divide, np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or, np.bitwise_xor, np.left_shift, np.right_shift, np.fmax, np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2, np.logical_and, np.logical_or, np.logical_xor, np.maximum, np.minimum, np.mod ] # These functions still return NotImplemented. Will be fixed in # future. # bad = [np.greater, np.greater_equal, np.less, np.less_equal, np.not_equal] a = np.array('1') b = 1 for f in binary_funcs: assert_raises(TypeError, f, a, b)
Example #17
Source File: test_topi_broadcast.py From incubator-tvm with Apache License 2.0 | 5 votes |
def test_shift(): # explicit specify the output type verify_broadcast_binary_ele( (2, 1, 2), None, topi.right_shift, np.right_shift, dtype="int32", rhs_min=0, rhs_max=32) verify_broadcast_binary_ele( (1, 2, 2), (2,), topi.left_shift, np.left_shift, dtype="int32", rhs_min=0, rhs_max=32) verify_broadcast_binary_ele( (1, 2, 2), (2,), topi.left_shift, np.left_shift, dtype="int8", rhs_min=0, rhs_max=32)
Example #18
Source File: load_syn.py From Gated2Depth with MIT License | 5 votes |
def load_gated(root_dir, sample, slice): path = os.path.join(root_dir, 'gated{}_10bit'.format(slice), sample + '.png') img = cv2.imread(path, -1) img = np.right_shift(img, 2).astype(np.uint8) # convert from 10bit to 8bit return img
Example #19
Source File: LMAarrayFile.py From lmatools with BSD 2-Clause "Simplified" License | 5 votes |
def countBits(values): # bit shifting routines are in numpy 1.4 from numpy import array, left_shift, right_shift v = array(values).astype('uint32') # Bit counting for a 32 bit unsigned integer. # there is a fully generic version of this method at # http://graphics.stanford.edu/~seander/bithacks.html#CountBitsSetParallel # Binary magic numbers method, also found in in pages 187-188 of Software Optimization Guide for AMD Athlon 64 and Opteron Processors. # The C version is: # v = v - ((v >> 1) & 0x55555555); # reuse input as temporary # v = (v & 0x33333333) + ((v >> 2) & 0x33333333); # temp # c = ((v + (v >> 4) & 0xF0F0F0F) * 0x1010101) >> 24; # count fives = int('0x55555555', base=16) threes = int('0x33333333', base=16) effs = int('0xF0F0F0F', base=16) ones = int('0x1010101', base=16) v = v - ( (right_shift(v, 1)) & fives); # reuse input as temporary v = (v & threes) + ( (right_shift(v,2)) & threes); # temp c = right_shift(((v + (right_shift(v,4)) & effs) * ones), 24); # count return c
Example #20
Source File: test_target_codegen_llvm.py From incubator-tvm with Apache License 2.0 | 5 votes |
def np_float2np_bf16(arr): ''' Convert a numpy array of float to a numpy array of bf16 in uint16''' orig = arr.view('<u4') bias = np.bitwise_and(np.right_shift(orig, 16), 1) + 0x7FFF return np.right_shift(orig + bias, 16).astype('uint16')
Example #21
Source File: display.py From push2-python with MIT License | 5 votes |
def rgb565_to_bgr565(rgb565_frame): r_filter = int('1111100000000000', 2) g_filter = int('0000011111100000', 2) b_filter = int('0000000000011111', 2) frame_r_filtered = numpy.bitwise_and(rgb565_frame, r_filter) frame_r_shifted = numpy.right_shift(frame_r_filtered, 11) # Shift bits so R compoenent goes to the right frame_g_filtered = numpy.bitwise_and(rgb565_frame, g_filter) frame_g_shifted = frame_g_filtered # No need to shift green, it stays in the same position frame_b_filtered = numpy.bitwise_and(rgb565_frame, b_filter) frame_b_shifted = numpy.left_shift(frame_b_filtered, 11) # Shift bits so B compoenent goes to the left return frame_r_shifted + frame_g_shifted + frame_b_shifted # Combine all channels # Non-vectorized function for converting from rgb to bgr565
Example #22
Source File: LMA_h5_write.py From lmatools with BSD 2-Clause "Simplified" License | 5 votes |
def countBits(values): # bit shifting routines are in numpy 1.4 from numpy import array, left_shift, right_shift v = array(values).astype('uint32') # Bit counting for a 32 bit unsigned integer. # there is a fully generic version of this method at # http://graphics.stanford.edu/~seander/bithacks.html#CountBitsSetParallel # Binary magic numbers method, also found in pages 187-188 of Software Optimization Guide for AMD Athlon 64 and Opteron Processors. # The C version is: # v = v - ((v >> 1) & 0x55555555); # reuse input as temporary # v = (v & 0x33333333) + ((v >> 2) & 0x33333333); # temp # c = ((v + (v >> 4) & 0xF0F0F0F) * 0x1010101) >> 24; # count fives = int('0x55555555', base=16) threes = int('0x33333333', base=16) effs = int('0xF0F0F0F', base=16) ones = int('0x1010101', base=16) v = v - ( (right_shift(v, 1)) & fives); # reuse input as temporary v = (v & threes) + ( (right_shift(v,2)) & threes); # temp c = right_shift(((v + (right_shift(v,4)) & effs) * ones), 24); # count return c
Example #23
Source File: walsh.py From geoist with MIT License | 5 votes |
def walsh_order(n): ''' generate 'natural','dyadic','sequence' ordering of walsh matrix. Args: n (int): degree of walsh matrix. ''' n = 2**np.ceil(np.log2(n)) n = int(n) n_bits = len(np.binary_repr(n))-1 print(n_bits) sequence_order = np.arange(n) tmp = np.right_shift(sequence_order,1) dyadic_order = np.bitwise_xor(sequence_order,tmp) natural_order = [int('{:0{width}b}'.format(i,width=n_bits)[::-1],2) for i in dyadic_order] return sequence_order,dyadic_order,natural_order
Example #24
Source File: readDatFiles.py From tierpsy-tracker with MIT License | 5 votes |
def read(self): self.curr_frame += 1 if self.curr_frame < self.num_frames: fname = self.files[self.dat_order[self.curr_frame]] # is this indexing correct, or do we need to shift down by one? bin_dat = np.fromfile(fname, np.uint8) # every 3 bytes will correspond two pixel levels. D1 = bin_dat[:-40:3] D2 = bin_dat[1:-40:3] D3 = bin_dat[2:-40:3] # the image format is mono 12 packed (see web) # the first and third bytes represent the higher bits of the pixel intensity # while the second byte is divided into the lower bits. D1s = np.left_shift(D1.astype(np.uint16), 4) + \ np.bitwise_and(D2, 15) D3s = np.left_shift(D3.astype(np.uint16), 4) + \ np.right_shift(D2, 4) # the pixels seemed to be organized in this order image_decoded = np.zeros((self.height, self.width), np.uint16) image_decoded[::-1, -2::-2] = D3s.reshape((self.height, -1)) image_decoded[::-1, ::-2] = D1s.reshape((self.height, -1)) return (1, image_decoded) else: return (0, [], [], [])
Example #25
Source File: load_real.py From Gated2Depth with MIT License | 5 votes |
def load_gated(root_dir, sample, slice): path = os.path.join(root_dir, 'gated{}_10bit'.format(slice), sample + '.png') img = cv2.imread(path, -1) img = np.right_shift(img, 2).astype(np.uint8) # convert from 10bit to 8bit return img
Example #26
Source File: exprsco.py From nesmdb with MIT License | 5 votes |
def exprsco_to_rawsco(exprsco, clock=1789773.): rate, nsamps, exprsco = exprsco m = exprsco[:, :3, 0] m_zero = np.where(m == 0) m = m.astype(np.float32) f = 440 * np.power(2, ((m - 69) / 12)) f_p, f_tr = f[:, :2], f[:, 2:] t_p = np.round((clock / (16 * f_p)) - 1) t_tr = np.round((clock / (32 * f_tr)) - 1) t = np.concatenate([t_p, t_tr], axis=1) t = t.astype(np.uint16) t[m_zero] = 0 th = np.right_shift(np.bitwise_and(t, 0b11100000000), 8) tl = np.bitwise_and(t, 0b00011111111) rawsco = np.zeros((exprsco.shape[0], 4, 4), dtype=np.uint8) rawsco[:, :, 2:] = exprsco[:, :, 1:] rawsco[:, :3, 0] = th rawsco[:, :3, 1] = tl rawsco[:, 3, 1:] = exprsco[:, 3, :] return (clock, rate, nsamps, rawsco)
Example #27
Source File: grid.py From gxpy with BSD 2-Clause "Simplified" License | 5 votes |
def _transform_color_int_to_rgba(np_values): np_values[np_values == gxapi.iDUMMY] = 0 a = (np.right_shift(np_values, 24) & 0xFF).astype(np.uint8) b = (np.right_shift(np_values, 16) & 0xFF).astype(np.uint8) g = (np.right_shift(np_values, 8) & 0xFF).astype(np.uint8) r = (np_values & 0xFF).astype(np.uint8) # the values for color grids actually do not contain alphas but just # 0 or 1 to indicate if the color is valid or not a[a > 0] = 255 return np.array([r, g, b, a]).transpose()
Example #28
Source File: cannonball_wrapper.py From agent-trainer with MIT License | 5 votes |
def _rgb_integers_to_components(self, rgb_integers): red_mask = 0x00FF0000 green_mask = 0x0000FF00 blue_mask = 0x000000FF masks = np.asarray([[red_mask, green_mask, blue_mask]]) masked_rgb_components = np.bitwise_and(rgb_integers, masks) red_shifted = np.right_shift(masked_rgb_components[:,0], 16) green_shifted = np.right_shift(masked_rgb_components[:,1], 8) blue_shifted = np.right_shift(masked_rgb_components[:,2], 0) return np.array([red_shifted, green_shifted, blue_shifted]).transpose()
Example #29
Source File: packer.py From blueoil with Apache License 2.0 | 5 votes |
def run(self, tensor: np.ndarray, data_format: str = 'NHWC') -> np.ndarray: """Pack a tensor. Args: tensor (np.ndarray): Input tensor. data_format (str): Order of dimension. This defaults to 'NHWC', where 'N' is the number of kernels, 'H' and 'W' are the height and width, and 'C' is the depth / the number of channels. Returns: np.ndarray: Quantized tensor. """ wordsize = self.wordsize if (tensor >= (2 ** self.bitwidth)).any(): raise ValueError("all value of input tensor must be less than bit width ({})".format(self.bitwidth)) output_size = tensor.size // wordsize output_size += 1 if tensor.size % wordsize != 0 else 0 output_size *= self.bitwidth tensor_flat = tensor.flatten(order='C').astype(np.uint32) output = np.zeros(output_size, dtype=np.uint32) oi = 0 for i in range(0, tensor.size, wordsize): if i + wordsize < tensor.size: sliced_tensor = tensor_flat[i:i + wordsize] else: sliced_tensor = tensor_flat[i:] for _ in range(0, self.bitwidth): output[oi] = self._pack_to_word(np.bitwise_and(sliced_tensor, 1)) oi += 1 sliced_tensor = np.right_shift(sliced_tensor, 1) return output.reshape([1, output_size])
Example #30
Source File: test_topi_broadcast.py From training_results_v0.6 with Apache License 2.0 | 5 votes |
def test_shift(): # explicit specify the output type verify_broadcast_binary_ele( (2, 1, 2), None, topi.right_shift, np.right_shift, dtype="int32", rhs_min=0, rhs_max=32) verify_broadcast_binary_ele( (1, 2, 2), (2,), topi.left_shift, np.left_shift, dtype="int32", rhs_min=0, rhs_max=32) verify_broadcast_binary_ele( (1, 2, 2), (2,), topi.left_shift, np.left_shift, dtype="int8", rhs_min=0, rhs_max=32)