Searched refs:np (Results 1 – 21 of 21) sorted by relevance
136 for (IwlanNetworkServiceProvider np : sIwlanNetworkServiceProviderList) { in onSubscriptionsChanged()137 np.subscriptionChanged(); in onSubscriptionsChanged()315 IwlanNetworkServiceProvider np = new IwlanNetworkServiceProvider(slotIndex, this); in onCreateNetworkServiceProvider() local316 sIwlanNetworkServiceProviderList.add(np); in onCreateNetworkServiceProvider()317 return np; in onCreateNetworkServiceProvider()340 for (IwlanNetworkServiceProvider np : sIwlanNetworkServiceProviderList) { in setNetworkConnected()341 np.notifyNetworkRegistrationInfoChanged(); in setNetworkConnected()345 public void removeNetworkServiceProvider(IwlanNetworkServiceProvider np) { in removeNetworkServiceProvider() argument346 sIwlanNetworkServiceProviderList.remove(np); in removeNetworkServiceProvider()375 for (IwlanNetworkServiceProvider np : sIwlanNetworkServiceProviderList) { in getNetworkServiceProvider()[all …]
16 import numpy as np namespace21 return np.array(tensor).reshape(tensor_shape).transpose(26 a = np.array(a).reshape(a_shape)27 b = np.array(b).reshape(b_shape)28 return np.concatenate((a, b), axis=2).flatten().tolist()31 return np.array(tensor).reshape(tensor_shape)[:, ::-1, :].flatten().tolist()34 tensor = np.array(tensor).reshape(tensor_shape)35 left, right = np.split(tensor, 2, axis=len(tensor_shape) - 1)
16 import numpy as np namespace21 return np.array(tensor).reshape(tensor_shape).transpose([1, 0, 226 a = np.array(a).reshape(a_shape)27 b = np.array(b).reshape(b_shape)28 return np.concatenate((a, b), axis=2).flatten().tolist()32 return np.array(tensor).reshape(tensor_shape)[:, ::-1, :].flatten().tolist()36 tensor = np.array(tensor).reshape(tensor_shape)37 left, right = np.split(tensor, 2, axis=len(tensor_shape) - 1)
17 import numpy as np namespace36 output0: np.pad([[[[1.0, 2.0, 3.0],138 output0: np.pad([[[[-127, -126, -125],
17 import numpy as np namespace20 values = list(np.linspace(-10, 10, num_values))
16 import numpy as np namespace43 return np.array(tensor).reshape([num_batches, max_time, input_size
209 ImageTypeShortBase *s, *ns, *ls, *p, *np; in BorderReduceOdd() local217 np = p + in->pitch; in BorderReduceOdd()220 for (; s < ls; s = ns, ns += scr->pitch, p = np, np += in->pitch) { in BorderReduceOdd()236 np = p + pitch2; in BorderReduceOdd()237 for (; s < ls; s = ns, ns += out->pitch, p = np, np += pitch2) { in BorderReduceOdd()
17 import numpy as np namespace32 output0: np.pad([[[[1, 2, 3],
17 import numpy as np namespace32 output0: np.pad([[[[1.0, 2.0, 3.0],
17 import numpy as np namespace36 output0: np.pad([[[[1.0, 2.0, 3.0],
16 import numpy as np namespace40 return np.array(tensor).reshape([num_batches, max_time,
37 import numpy as np namespace67 v = np.round(v)71 v = np.minimum(np.maximum(v, 0), 255)73 v = np.minimum(np.maximum(v, 0), 65535)75 v = np.minimum(np.maximum(v, -127), 127)77 v = np.maximum(v, 0)79 v = np.minimum(np.maximum(v, -128), 127)250 return np.array(self.scales).reshape(bshape)281 return np.array(self.value).reshape(self.type.dimensions)793 v = Dequantize(op.GetValueAsNumpy().astype(np.float32), op.type)[all …]
181 @NonNull NetworkProvider np) in TestNetworkAgent() argument183 super(context, looper, TEST_NETWORK_LOGTAG, nc, lp, NETWORK_SCORE, config, np); in TestNetworkAgent()
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1dictionary=main:lv,locale=lv,description=Latviešu,date=1393228136, ...
... ,flags=,originalFreq=163 104 word=np,f=163,flags=abbreviation,originalFreq ...