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100<div class="title">Conv2D.cpp File Reference</div> </div>
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102<div class="contents">
103<div class="textblock"><code>#include &lt;boost/test/unit_test.hpp&gt;</code><br />
104<code>#include &quot;<a class="el" href="_parser_flatbuffers_fixture_8hpp_source.xhtml">ParserFlatbuffersFixture.hpp</a>&quot;</code><br />
105<code>#include &quot;<a class="el" href="_tf_lite_parser_8hpp_source.xhtml">../TfLiteParser.hpp</a>&quot;</code><br />
106<code>#include &lt;sstream&gt;</code><br />
107</div>
108<p><a href="armnn_tf_lite_parser_2test_2_conv2_d_8cpp_source.xhtml">Go to the source code of this file.</a></p>
109<table class="memberdecls">
110<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="func-members"></a>
111Functions</h2></td></tr>
112<tr class="memitem:afcc317a537dfa8ab47071d5c464bad43"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="armnn_tf_lite_parser_2test_2_conv2_d_8cpp.xhtml#afcc317a537dfa8ab47071d5c464bad43">BOOST_FIXTURE_TEST_CASE</a> (ParseSimpleConv2D, SimpleConv2DFixture)</td></tr>
113<tr class="separator:afcc317a537dfa8ab47071d5c464bad43"><td class="memSeparator" colspan="2">&#160;</td></tr>
114<tr class="memitem:a1f8274795936acc6692b9e18a2d7f7a0"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="armnn_tf_lite_parser_2test_2_conv2_d_8cpp.xhtml#a1f8274795936acc6692b9e18a2d7f7a0">BOOST_FIXTURE_TEST_CASE</a> (ParseConv2DWithBias, SimpleConv2DWithBiasesFixture)</td></tr>
115<tr class="separator:a1f8274795936acc6692b9e18a2d7f7a0"><td class="memSeparator" colspan="2">&#160;</td></tr>
116<tr class="memitem:a37807b86838def29aa4a342b5ee11a1e"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="armnn_tf_lite_parser_2test_2_conv2_d_8cpp.xhtml#a37807b86838def29aa4a342b5ee11a1e">BOOST_FIXTURE_TEST_CASE</a> (ParseConv2D_112x112_out, Conv2DShapeTestFixture)</td></tr>
117<tr class="separator:a37807b86838def29aa4a342b5ee11a1e"><td class="memSeparator" colspan="2">&#160;</td></tr>
118<tr class="memitem:aeae31b1eb962892a52153424119c87e9"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="armnn_tf_lite_parser_2test_2_conv2_d_8cpp.xhtml#aeae31b1eb962892a52153424119c87e9">BOOST_FIXTURE_TEST_CASE</a> (ParseConv2DAndReluWithBias, ReluConv2DWithBiasesFixture)</td></tr>
119<tr class="separator:aeae31b1eb962892a52153424119c87e9"><td class="memSeparator" colspan="2">&#160;</td></tr>
120<tr class="memitem:a16517509d65fc4291eb40bcc285c03fd"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="armnn_tf_lite_parser_2test_2_conv2_d_8cpp.xhtml#a16517509d65fc4291eb40bcc285c03fd">BOOST_FIXTURE_TEST_CASE</a> (ParseConv2DAndRelu6WithBias, Relu6Conv2DWithBiasesFixture)</td></tr>
121<tr class="separator:a16517509d65fc4291eb40bcc285c03fd"><td class="memSeparator" colspan="2">&#160;</td></tr>
122</table>
123<h2 class="groupheader">Function Documentation</h2>
124<a id="afcc317a537dfa8ab47071d5c464bad43"></a>
125<h2 class="memtitle"><span class="permalink"><a href="#afcc317a537dfa8ab47071d5c464bad43">&#9670;&nbsp;</a></span>BOOST_FIXTURE_TEST_CASE() <span class="overload">[1/5]</span></h2>
126
127<div class="memitem">
128<div class="memproto">
129 <table class="memname">
130 <tr>
131 <td class="memname">BOOST_FIXTURE_TEST_CASE </td>
132 <td>(</td>
133 <td class="paramtype">ParseSimpleConv2D&#160;</td>
134 <td class="paramname">, </td>
135 </tr>
136 <tr>
137 <td class="paramkey"></td>
138 <td></td>
139 <td class="paramtype">SimpleConv2DFixture&#160;</td>
140 <td class="paramname">&#160;</td>
141 </tr>
142 <tr>
143 <td></td>
144 <td>)</td>
145 <td></td><td></td>
146 </tr>
147 </table>
148</div><div class="memdoc">
149
150<p class="definition">Definition at line <a class="el" href="armnn_tf_lite_parser_2test_2_conv2_d_8cpp_source.xhtml#l00090">90</a> of file <a class="el" href="armnn_tf_lite_parser_2test_2_conv2_d_8cpp_source.xhtml">Conv2D.cpp</a>.</p>
151<div class="fragment"><div class="line"><a name="l00091"></a><span class="lineno"> 91</span>&#160;{</div><div class="line"><a name="l00092"></a><span class="lineno"> 92</span>&#160; RunTest&lt;4, armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l00093"></a><span class="lineno"> 93</span>&#160; 0,</div><div class="line"><a name="l00094"></a><span class="lineno"> 94</span>&#160; {</div><div class="line"><a name="l00095"></a><span class="lineno"> 95</span>&#160; 1, 2, 3,</div><div class="line"><a name="l00096"></a><span class="lineno"> 96</span>&#160; 4, 5, 6,</div><div class="line"><a name="l00097"></a><span class="lineno"> 97</span>&#160; 7, 8, 9,</div><div class="line"><a name="l00098"></a><span class="lineno"> 98</span>&#160; },</div><div class="line"><a name="l00099"></a><span class="lineno"> 99</span>&#160; <span class="comment">// because of the output scaling we need to take half of the values</span></div><div class="line"><a name="l00100"></a><span class="lineno"> 100</span>&#160; {</div><div class="line"><a name="l00101"></a><span class="lineno"> 101</span>&#160; (1*2 + 2*1 + 3*0 +</div><div class="line"><a name="l00102"></a><span class="lineno"> 102</span>&#160; 4*6 + 5*2 + 6*1 +</div><div class="line"><a name="l00103"></a><span class="lineno"> 103</span>&#160; 7*4 + 8*1 + 9*2) /2</div><div class="line"><a name="l00104"></a><span class="lineno"> 104</span>&#160; });</div><div class="line"><a name="l00105"></a><span class="lineno"> 105</span>&#160;}</div></div><!-- fragment -->
152</div>
153</div>
154<a id="a1f8274795936acc6692b9e18a2d7f7a0"></a>
155<h2 class="memtitle"><span class="permalink"><a href="#a1f8274795936acc6692b9e18a2d7f7a0">&#9670;&nbsp;</a></span>BOOST_FIXTURE_TEST_CASE() <span class="overload">[2/5]</span></h2>
156
157<div class="memitem">
158<div class="memproto">
159 <table class="memname">
160 <tr>
161 <td class="memname">BOOST_FIXTURE_TEST_CASE </td>
162 <td>(</td>
163 <td class="paramtype">ParseConv2DWithBias&#160;</td>
164 <td class="paramname">, </td>
165 </tr>
166 <tr>
167 <td class="paramkey"></td>
168 <td></td>
169 <td class="paramtype">SimpleConv2DWithBiasesFixture&#160;</td>
170 <td class="paramname">&#160;</td>
171 </tr>
172 <tr>
173 <td></td>
174 <td>)</td>
175 <td></td><td></td>
176 </tr>
177 </table>
178</div><div class="memdoc">
179
180<p class="definition">Definition at line <a class="el" href="armnn_tf_lite_parser_2test_2_conv2_d_8cpp_source.xhtml#l00220">220</a> of file <a class="el" href="armnn_tf_lite_parser_2test_2_conv2_d_8cpp_source.xhtml">Conv2D.cpp</a>.</p>
181<div class="fragment"><div class="line"><a name="l00221"></a><span class="lineno"> 221</span>&#160;{</div><div class="line"><a name="l00222"></a><span class="lineno"> 222</span>&#160; RunTest&lt;4, armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l00223"></a><span class="lineno"> 223</span>&#160; 0,</div><div class="line"><a name="l00224"></a><span class="lineno"> 224</span>&#160; {</div><div class="line"><a name="l00225"></a><span class="lineno"> 225</span>&#160; 1, 2,</div><div class="line"><a name="l00226"></a><span class="lineno"> 226</span>&#160; 3, 4,</div><div class="line"><a name="l00227"></a><span class="lineno"> 227</span>&#160; },</div><div class="line"><a name="l00228"></a><span class="lineno"> 228</span>&#160; <span class="comment">// because of the output scaling we need to take half of the values</span></div><div class="line"><a name="l00229"></a><span class="lineno"> 229</span>&#160; {</div><div class="line"><a name="l00230"></a><span class="lineno"> 230</span>&#160; (1*2 + 2*1 + 3*0 + 4*6 + 10)/2,</div><div class="line"><a name="l00231"></a><span class="lineno"> 231</span>&#160; (2*2 + 0*1 + 4*0 + 0*6 + 10)/2,</div><div class="line"><a name="l00232"></a><span class="lineno"> 232</span>&#160; (3*2 + 4*1 + 0*0 + 0*6 + 10)/2,</div><div class="line"><a name="l00233"></a><span class="lineno"> 233</span>&#160; (4*2 + 0*1 + 0*0 + 0*6 + 10)/2</div><div class="line"><a name="l00234"></a><span class="lineno"> 234</span>&#160; });</div><div class="line"><a name="l00235"></a><span class="lineno"> 235</span>&#160;}</div></div><!-- fragment -->
182</div>
183</div>
184<a id="a37807b86838def29aa4a342b5ee11a1e"></a>
185<h2 class="memtitle"><span class="permalink"><a href="#a37807b86838def29aa4a342b5ee11a1e">&#9670;&nbsp;</a></span>BOOST_FIXTURE_TEST_CASE() <span class="overload">[3/5]</span></h2>
186
187<div class="memitem">
188<div class="memproto">
189 <table class="memname">
190 <tr>
191 <td class="memname">BOOST_FIXTURE_TEST_CASE </td>
192 <td>(</td>
193 <td class="paramtype">ParseConv2D_112x112_out&#160;</td>
194 <td class="paramname">, </td>
195 </tr>
196 <tr>
197 <td class="paramkey"></td>
198 <td></td>
199 <td class="paramtype">Conv2DShapeTestFixture&#160;</td>
200 <td class="paramname">&#160;</td>
201 </tr>
202 <tr>
203 <td></td>
204 <td>)</td>
205 <td></td><td></td>
206 </tr>
207 </table>
208</div><div class="memdoc">
209
210<p class="definition">Definition at line <a class="el" href="armnn_tf_lite_parser_2test_2_conv2_d_8cpp_source.xhtml#l00265">265</a> of file <a class="el" href="armnn_tf_lite_parser_2test_2_conv2_d_8cpp_source.xhtml">Conv2D.cpp</a>.</p>
211<div class="fragment"><div class="line"><a name="l00266"></a><span class="lineno"> 266</span>&#160;{</div><div class="line"><a name="l00267"></a><span class="lineno"> 267</span>&#160;}</div></div><!-- fragment -->
212</div>
213</div>
214<a id="aeae31b1eb962892a52153424119c87e9"></a>
215<h2 class="memtitle"><span class="permalink"><a href="#aeae31b1eb962892a52153424119c87e9">&#9670;&nbsp;</a></span>BOOST_FIXTURE_TEST_CASE() <span class="overload">[4/5]</span></h2>
216
217<div class="memitem">
218<div class="memproto">
219 <table class="memname">
220 <tr>
221 <td class="memname">BOOST_FIXTURE_TEST_CASE </td>
222 <td>(</td>
223 <td class="paramtype">ParseConv2DAndReluWithBias&#160;</td>
224 <td class="paramname">, </td>
225 </tr>
226 <tr>
227 <td class="paramkey"></td>
228 <td></td>
229 <td class="paramtype">ReluConv2DWithBiasesFixture&#160;</td>
230 <td class="paramname">&#160;</td>
231 </tr>
232 <tr>
233 <td></td>
234 <td>)</td>
235 <td></td><td></td>
236 </tr>
237 </table>
238</div><div class="memdoc">
239
240<p class="definition">Definition at line <a class="el" href="armnn_tf_lite_parser_2test_2_conv2_d_8cpp_source.xhtml#l00287">287</a> of file <a class="el" href="armnn_tf_lite_parser_2test_2_conv2_d_8cpp_source.xhtml">Conv2D.cpp</a>.</p>
241<div class="fragment"><div class="line"><a name="l00288"></a><span class="lineno"> 288</span>&#160;{</div><div class="line"><a name="l00289"></a><span class="lineno"> 289</span>&#160; uint8_t bias = 16;</div><div class="line"><a name="l00290"></a><span class="lineno"> 290</span>&#160; uint8_t outZero = 20;</div><div class="line"><a name="l00291"></a><span class="lineno"> 291</span>&#160; uint8_t fz = 4; <span class="comment">// filter zero point</span></div><div class="line"><a name="l00292"></a><span class="lineno"> 292</span>&#160;</div><div class="line"><a name="l00293"></a><span class="lineno"> 293</span>&#160; RunTest&lt;4, armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l00294"></a><span class="lineno"> 294</span>&#160; 0,</div><div class="line"><a name="l00295"></a><span class="lineno"> 295</span>&#160; {</div><div class="line"><a name="l00296"></a><span class="lineno"> 296</span>&#160; 1, 2,</div><div class="line"><a name="l00297"></a><span class="lineno"> 297</span>&#160; 4, 8,</div><div class="line"><a name="l00298"></a><span class="lineno"> 298</span>&#160; },</div><div class="line"><a name="l00299"></a><span class="lineno"> 299</span>&#160; <span class="comment">// factors to consider:</span></div><div class="line"><a name="l00300"></a><span class="lineno"> 300</span>&#160; <span class="comment">// - the filter zero point is non zero, hence the (x-fz)</span></div><div class="line"><a name="l00301"></a><span class="lineno"> 301</span>&#160; <span class="comment">// - the output scale is 2 hence the /2</span></div><div class="line"><a name="l00302"></a><span class="lineno"> 302</span>&#160; <span class="comment">// - output zero point is non zero, hence the +outZero</span></div><div class="line"><a name="l00303"></a><span class="lineno"> 303</span>&#160; <span class="comment">// - RELU cuts negative values and then we add the output zero point</span></div><div class="line"><a name="l00304"></a><span class="lineno"> 304</span>&#160; {</div><div class="line"><a name="l00305"></a><span class="lineno"> 305</span>&#160; std::max(outZero, static_cast&lt;uint8_t&gt;((1*(2-fz) + 2*(1-fz) + 4*(0-fz) + 8*(6-fz) + bias)/2 + outZero)),</div><div class="line"><a name="l00306"></a><span class="lineno"> 306</span>&#160; std::max(outZero, static_cast&lt;uint8_t&gt;((2*(2-fz) + 0*(1-fz) + 8*(0-fz) + 0*(6-fz) + bias)/2 + outZero)),</div><div class="line"><a name="l00307"></a><span class="lineno"> 307</span>&#160; std::max(outZero, static_cast&lt;uint8_t&gt;((4*(2-fz) + 8*(1-fz) + 0*(0-fz) + 0*(6-fz) + bias)/2 + outZero)),</div><div class="line"><a name="l00308"></a><span class="lineno"> 308</span>&#160; std::max(outZero, static_cast&lt;uint8_t&gt;((8*(2-fz) + 0*(1-fz) + 0*(0-fz) + 0*(6-fz) + bias)/2 + outZero))</div><div class="line"><a name="l00309"></a><span class="lineno"> 309</span>&#160; });</div><div class="line"><a name="l00310"></a><span class="lineno"> 310</span>&#160;}</div></div><!-- fragment -->
242</div>
243</div>
244<a id="a16517509d65fc4291eb40bcc285c03fd"></a>
245<h2 class="memtitle"><span class="permalink"><a href="#a16517509d65fc4291eb40bcc285c03fd">&#9670;&nbsp;</a></span>BOOST_FIXTURE_TEST_CASE() <span class="overload">[5/5]</span></h2>
246
247<div class="memitem">
248<div class="memproto">
249 <table class="memname">
250 <tr>
251 <td class="memname">BOOST_FIXTURE_TEST_CASE </td>
252 <td>(</td>
253 <td class="paramtype">ParseConv2DAndRelu6WithBias&#160;</td>
254 <td class="paramname">, </td>
255 </tr>
256 <tr>
257 <td class="paramkey"></td>
258 <td></td>
259 <td class="paramtype">Relu6Conv2DWithBiasesFixture&#160;</td>
260 <td class="paramname">&#160;</td>
261 </tr>
262 <tr>
263 <td></td>
264 <td>)</td>
265 <td></td><td></td>
266 </tr>
267 </table>
268</div><div class="memdoc">
269
270<p class="definition">Definition at line <a class="el" href="armnn_tf_lite_parser_2test_2_conv2_d_8cpp_source.xhtml#l00330">330</a> of file <a class="el" href="armnn_tf_lite_parser_2test_2_conv2_d_8cpp_source.xhtml">Conv2D.cpp</a>.</p>
271
272<p class="reference">References <a class="el" href="_profiler_tests_8cpp.xhtml#af7f71af5c6c124222dd1c42c5df892f4">BOOST_AUTO_TEST_SUITE_END()</a>.</p>
273<div class="fragment"><div class="line"><a name="l00331"></a><span class="lineno"> 331</span>&#160;{</div><div class="line"><a name="l00332"></a><span class="lineno"> 332</span>&#160; uint8_t relu6Min = 6 / 2; <span class="comment">// divide by output scale</span></div><div class="line"><a name="l00333"></a><span class="lineno"> 333</span>&#160;</div><div class="line"><a name="l00334"></a><span class="lineno"> 334</span>&#160; RunTest&lt;4, armnn::DataType::QAsymmU8&gt;(</div><div class="line"><a name="l00335"></a><span class="lineno"> 335</span>&#160; 0,</div><div class="line"><a name="l00336"></a><span class="lineno"> 336</span>&#160; {</div><div class="line"><a name="l00337"></a><span class="lineno"> 337</span>&#160; 1, 2,</div><div class="line"><a name="l00338"></a><span class="lineno"> 338</span>&#160; 4, 1,</div><div class="line"><a name="l00339"></a><span class="lineno"> 339</span>&#160; },</div><div class="line"><a name="l00340"></a><span class="lineno"> 340</span>&#160; <span class="comment">// factors to consider:</span></div><div class="line"><a name="l00341"></a><span class="lineno"> 341</span>&#160; <span class="comment">// - the output scale is 2 hence the /2</span></div><div class="line"><a name="l00342"></a><span class="lineno"> 342</span>&#160; <span class="comment">// - RELU6 cuts output values at +6</span></div><div class="line"><a name="l00343"></a><span class="lineno"> 343</span>&#160; {</div><div class="line"><a name="l00344"></a><span class="lineno"> 344</span>&#160; std::min(relu6Min, static_cast&lt;uint8_t&gt;((1*2 + 2*1 + 4*0 + 1*6)/2)),</div><div class="line"><a name="l00345"></a><span class="lineno"> 345</span>&#160; std::min(relu6Min, static_cast&lt;uint8_t&gt;((2*2 + 0*1 + 1*0 + 0*6)/2)),</div><div class="line"><a name="l00346"></a><span class="lineno"> 346</span>&#160; std::min(relu6Min, static_cast&lt;uint8_t&gt;((4*2 + 1*1 + 0*0 + 0*6)/2)),</div><div class="line"><a name="l00347"></a><span class="lineno"> 347</span>&#160; std::min(relu6Min, static_cast&lt;uint8_t&gt;((1*2 + 0*1 + 0*0 + 0*6)/2))</div><div class="line"><a name="l00348"></a><span class="lineno"> 348</span>&#160; });</div><div class="line"><a name="l00349"></a><span class="lineno"> 349</span>&#160;}</div></div><!-- fragment -->
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