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86+ < span > </ span > < span class ="c1 "> # -*- coding: utf-8 -*-</ span >
87+ < span class ="c1 "> # *****************************************************************************</ span >
88+ < span class ="c1 "> # Copyright (c) 2016-2024, Intel Corporation</ span >
89+ < span class ="c1 "> # All rights reserved.</ span >
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96+ < span class ="c1 "> # this list of conditions and the following disclaimer in the documentation</ span >
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99+ < span class ="c1 "> # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"</ span >
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111+
112+ < span class ="sd "> """</ span >
113+ < span class ="sd "> Interface of the counting function of the dpnp</ span >
114+
115+ < span class ="sd "> Notes</ span >
116+ < span class ="sd "> -----</ span >
117+ < span class ="sd "> This module is a face or public interface file for the library</ span >
118+ < span class ="sd "> it contains:</ span >
119+ < span class ="sd "> - Interface functions</ span >
120+ < span class ="sd "> - documentation for the functions</ span >
121+ < span class ="sd "> - The functions parameters check</ span >
122+
123+ < span class ="sd "> """</ span >
124+
125+ < span class ="kn "> import</ span > < span class ="nn "> dpctl.tensor</ span > < span class ="k "> as</ span > < span class ="nn "> dpt</ span >
126+
127+ < span class ="kn "> import</ span > < span class ="nn "> dpnp</ span >
128+
129+ < span class ="n "> __all__</ span > < span class ="o "> =</ span > < span class ="p "> [</ span > < span class ="s2 "> "count_nonzero"</ span > < span class ="p "> ]</ span >
130+
131+
132+ < div class ="viewcode-block " id ="count_nonzero ">
133+ < a class ="viewcode-back " href ="../../reference/generated/dpnp.count_nonzero.html#dpnp.count_nonzero "> [docs]</ a >
134+ < span class ="k "> def</ span > < span class ="nf "> count_nonzero</ span > < span class ="p "> (</ span > < span class ="n "> a</ span > < span class ="p "> ,</ span > < span class ="n "> axis</ span > < span class ="o "> =</ span > < span class ="kc "> None</ span > < span class ="p "> ,</ span > < span class ="o "> *</ span > < span class ="p "> ,</ span > < span class ="n "> keepdims</ span > < span class ="o "> =</ span > < span class ="kc "> False</ span > < span class ="p "> ,</ span > < span class ="n "> out</ span > < span class ="o "> =</ span > < span class ="kc "> None</ span > < span class ="p "> ):</ span >
135+ < span class ="w "> </ span > < span class ="sd "> """</ span >
136+ < span class ="sd "> Counts the number of non-zero values in the array `a`.</ span >
137+
138+ < span class ="sd "> For full documentation refer to :obj:`numpy.count_nonzero`.</ span >
139+
140+ < span class ="sd "> Parameters</ span >
141+ < span class ="sd "> ----------</ span >
142+ < span class ="sd "> a : {dpnp.ndarray, usm_ndarray}</ span >
143+ < span class ="sd "> The array for which to count non-zeros.</ span >
144+ < span class ="sd "> axis : {None, int, tuple}, optional</ span >
145+ < span class ="sd "> Axis or tuple of axes along which to count non-zeros.</ span >
146+ < span class ="sd "> Default value means that non-zeros will be counted along a flattened</ span >
147+ < span class ="sd "> version of `a`.</ span >
148+ < span class ="sd "> Default: ``None``.</ span >
149+ < span class ="sd "> keepdims : bool, optional</ span >
150+ < span class ="sd "> If this is set to ``True``, the axes that are counted are left in the</ span >
151+ < span class ="sd "> result as dimensions with size one. With this option, the result will</ span >
152+ < span class ="sd "> broadcast correctly against the input array.</ span >
153+ < span class ="sd "> Default: ``False``.</ span >
154+ < span class ="sd "> out : {None, dpnp.ndarray, usm_ndarray}, optional</ span >
155+ < span class ="sd "> The array into which the result is written. The data type of `out` must</ span >
156+ < span class ="sd "> match the expected shape and the expected data type of the result.</ span >
157+ < span class ="sd "> If ``None`` then a new array is returned.</ span >
158+ < span class ="sd "> Default: ``None``.</ span >
159+
160+ < span class ="sd "> Returns</ span >
161+ < span class ="sd "> -------</ span >
162+ < span class ="sd "> out : dpnp.ndarray</ span >
163+ < span class ="sd "> Number of non-zero values in the array along a given axis.</ span >
164+ < span class ="sd "> Otherwise, a zero-dimensional array with the total number of non-zero</ span >
165+ < span class ="sd "> values in the array is returned.</ span >
166+
167+ < span class ="sd "> See Also</ span >
168+ < span class ="sd "> --------</ span >
169+ < span class ="sd "> :obj:`dpnp.nonzero` : Return the coordinates of all the non-zero values.</ span >
170+
171+ < span class ="sd "> Examples</ span >
172+ < span class ="sd "> --------</ span >
173+ < span class ="sd "> >>> import dpnp as np</ span >
174+ < span class ="sd "> >>> np.count_nonzero(np.eye(4))</ span >
175+ < span class ="sd "> array(4)</ span >
176+ < span class ="sd "> >>> a = np.array([[0, 1, 7, 0],</ span >
177+ < span class ="sd "> [3, 0, 2, 19]])</ span >
178+ < span class ="sd "> >>> np.count_nonzero(a)</ span >
179+ < span class ="sd "> array(5)</ span >
180+ < span class ="sd "> >>> np.count_nonzero(a, axis=0)</ span >
181+ < span class ="sd "> array([1, 1, 2, 1])</ span >
182+ < span class ="sd "> >>> np.count_nonzero(a, axis=1)</ span >
183+ < span class ="sd "> array([2, 3])</ span >
184+ < span class ="sd "> >>> np.count_nonzero(a, axis=1, keepdims=True)</ span >
185+ < span class ="sd "> array([[2],</ span >
186+ < span class ="sd "> [3]])</ span >
187+
188+ < span class ="sd "> """</ span >
189+
190+ < span class ="n "> usm_a</ span > < span class ="o "> =</ span > < span class ="n "> dpnp</ span > < span class ="o "> .</ span > < span class ="n "> get_usm_ndarray</ span > < span class ="p "> (</ span > < span class ="n "> a</ span > < span class ="p "> )</ span >
191+ < span class ="n "> usm_out</ span > < span class ="o "> =</ span > < span class ="kc "> None</ span > < span class ="k "> if</ span > < span class ="n "> out</ span > < span class ="ow "> is</ span > < span class ="kc "> None</ span > < span class ="k "> else</ span > < span class ="n "> dpnp</ span > < span class ="o "> .</ span > < span class ="n "> get_usm_ndarray</ span > < span class ="p "> (</ span > < span class ="n "> out</ span > < span class ="p "> )</ span >
192+
193+ < span class ="n "> usm_res</ span > < span class ="o "> =</ span > < span class ="n "> dpt</ span > < span class ="o "> .</ span > < span class ="n "> count_nonzero</ span > < span class ="p "> (</ span >
194+ < span class ="n "> usm_a</ span > < span class ="p "> ,</ span > < span class ="n "> axis</ span > < span class ="o "> =</ span > < span class ="n "> axis</ span > < span class ="p "> ,</ span > < span class ="n "> keepdims</ span > < span class ="o "> =</ span > < span class ="n "> keepdims</ span > < span class ="p "> ,</ span > < span class ="n "> out</ span > < span class ="o "> =</ span > < span class ="n "> usm_out</ span >
195+ < span class ="p "> )</ span >
196+ < span class ="k "> return</ span > < span class ="n "> dpnp</ span > < span class ="o "> .</ span > < span class ="n "> get_result_array</ span > < span class ="p "> (</ span > < span class ="n "> usm_res</ span > < span class ="p "> ,</ span > < span class ="n "> out</ span > < span class ="p "> )</ span > </ div >
197+
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