Searched refs:output (Results 1 - 25 of 863) sorted by relevance

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/frameworks/base/core/tests/coretests/src/com/android/internal/http/multipart/
H A DMultipartTest.java60 StringBuffer output = new StringBuffer();
62 output.append("--");
63 output.append(boundry);
64 output.append(CRLF);
66 output.append("Content-Disposition: form-data; name=\"stringpart\"");
67 output.append(CRLF);
68 output.append("Content-Type: text/plain; charset=US-ASCII");
69 output.append(CRLF);
70 output.append("Content-Transfer-Encoding: 8bit");
71 output
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/frameworks/base/tests/Camera2Tests/SmartCamera/SimpleCamera/src/androidx/media/filterfw/
H A DColorSpace.java33 * YUV to RGB conversion is done using the ITU-R BT.601 transformation. The output buffer must
37 * @param output buffer to hold RGBA8888 data.
42 ByteBuffer input, ByteBuffer output, int width, int height) {
44 expectOutputSize(output, width * height * 4);
45 nativeYuv420pToRgba8888(input, output, width, height);
51 * The input data is expected to be encoded in 8-bit interleaved ARGB channels. The output
52 * buffer must be large enough to hold the data. The output buffer may be the same as the
56 * @param output buffer to hold RGBA8888 data.
61 ByteBuffer input, ByteBuffer output, int width, int height) {
63 expectOutputSize(output, widt
41 convertYuv420pToRgba8888( ByteBuffer input, ByteBuffer output, int width, int height) argument
60 convertArgb8888ToRgba8888( ByteBuffer input, ByteBuffer output, int width, int height) argument
79 convertRgba8888ToHsva8888( ByteBuffer input, ByteBuffer output, int width, int height) argument
98 convertRgba8888ToYcbcra8888( ByteBuffer input, ByteBuffer output, int width, int height) argument
113 expectOutputSize(ByteBuffer output, int expectedSize) argument
121 nativeYuv420pToRgba8888( ByteBuffer input, ByteBuffer output, int width, int height) argument
124 nativeArgb8888ToRgba8888( ByteBuffer input, ByteBuffer output, int width, int height) argument
127 nativeRgba8888ToHsva8888( ByteBuffer input, ByteBuffer output, int width, int height) argument
130 nativeRgba8888ToYcbcra8888( ByteBuffer input, ByteBuffer output, int width, int height) argument
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/frameworks/ml/nn/runtime/test/specs/V1_0/
H A Ddepth_to_space_float_1.mod.py4 output = Output("output", "TENSOR_FLOAT32", "{1, 2, 2, 2}") variable
6 model = model.Operation("DEPTH_TO_SPACE", i1, block).To(output)
12 output0 = {output: # output 0
H A Ddepth_to_space_float_2.mod.py4 output = Output("output", "TENSOR_FLOAT32", "{1, 4, 4, 1}") variable
6 model = model.Operation("DEPTH_TO_SPACE", i1, block).To(output)
12 output0 = {output: # output 0
H A Ddepth_to_space_float_3.mod.py4 output = Output("output", "TENSOR_FLOAT32", "{1, 4, 4, 2}") variable
6 model = model.Operation("DEPTH_TO_SPACE", i1, block).To(output)
16 output0 = {output: # output 0
H A Ddepth_to_space_quant8_1.mod.py4 output = Output("output", "TENSOR_QUANT8_ASYMM", "{1, 2, 2, 2}, 0.5f, 0") variable
6 model = model.Operation("DEPTH_TO_SPACE", i1, block).To(output)
12 output0 = {output: # output 0
H A Ddepth_to_space_quant8_2.mod.py4 output = Output("output", "TENSOR_QUANT8_ASYMM", "{1, 4, 4, 1}, 0.5f, 0") variable
6 model = model.Operation("DEPTH_TO_SPACE", i1, block).To(output)
12 output0 = {output: # output 0
H A Dlocal_response_norm_float_1.mod.py7 output = Output("output", "TENSOR_FLOAT32", "{1, 1, 1, 6}") variable
9 model = model.Operation("LOCAL_RESPONSE_NORMALIZATION", i1, radius, bias, alpha, beta).To(output)
15 output0 = {output: # output 0
H A Dlocal_response_norm_float_2.mod.py7 output = Output("output", "TENSOR_FLOAT32", "{1, 1, 1, 6}") variable
9 model = model.Operation("LOCAL_RESPONSE_NORMALIZATION", i1, radius, bias, alpha, beta).To(output)
15 output0 = {output: # output 0
H A Dlocal_response_norm_float_3.mod.py7 output = Output("output", "TENSOR_FLOAT32", "{1, 1, 1, 6}") variable
9 model = model.Operation("LOCAL_RESPONSE_NORMALIZATION", i1, radius, bias, alpha, beta).To(output)
15 output0 = {output: # output 0
H A Dlocal_response_norm_float_4.mod.py7 output = Output("output", "TENSOR_FLOAT32", "{1, 1, 1, 6}") variable
9 model = model.Operation("LOCAL_RESPONSE_NORMALIZATION", i1, radius, bias, alpha, beta).To(output)
15 output0 = {output: # output 0
H A Dsoftmax_float_1.mod.py6 output = Output("output", "TENSOR_FLOAT32", "{1, 4}") variable
9 model = model.Operation("SOFTMAX", i1, beta).To(output)
14 output0 = {output: [.25, .25, .25, .25]}
H A Dsoftmax_float_2.mod.py6 output = Output("output", "TENSOR_FLOAT32", "{2, 5}") variable
9 model = model.Operation("SOFTMAX", i1, beta).To(output)
16 output0 = {output:
H A Dsoftmax_quant8_1.mod.py6 output = Output("output", "TENSOR_QUANT8_ASYMM", "{1, 4}, 0.00390625f, 0") variable
9 model = model.Operation("SOFTMAX", i1, beta).To(output)
14 output0 = {output: [64, 64, 64, 64]}
H A Dsoftmax_quant8_2.mod.py6 output = Output("output", "TENSOR_QUANT8_ASYMM", "{2, 5}, 0.00390625f, 0") variable
9 model = model.Operation("SOFTMAX", i1, beta).To(output)
16 output0 = {output:
H A Dspace_to_depth_float_1.mod.py4 output = Output("output", "TENSOR_FLOAT32", "{1, 1, 1, 8}") variable
6 model = model.Operation("SPACE_TO_DEPTH", i1, block).To(output)
12 output0 = {output: # output 0
H A Dspace_to_depth_float_2.mod.py4 output = Output("output", "TENSOR_FLOAT32", "{1, 2, 2, 4}") variable
6 model = model.Operation("SPACE_TO_DEPTH", i1, block).To(output)
12 output0 = {output: # output 0
H A Dspace_to_depth_float_3.mod.py4 output = Output("output", "TENSOR_FLOAT32", "{1, 2, 2, 8}") variable
6 model = model.Operation("SPACE_TO_DEPTH", i1, block).To(output)
15 output0 = {output: # output 0
H A Dspace_to_depth_quant8_1.mod.py4 output = Output("output", "TENSOR_QUANT8_ASYMM", "{1, 1, 1, 8}, 0.5f, 0") variable
6 model = model.Operation("SPACE_TO_DEPTH", i1, block).To(output)
12 output0 = {output: # output 0
H A Dspace_to_depth_quant8_2.mod.py4 output = Output("output", "TENSOR_QUANT8_ASYMM", "{1, 2, 2, 4}, 0.5f, 0") variable
6 model = model.Operation("SPACE_TO_DEPTH", i1, block).To(output)
12 output0 = {output: # output 0
/frameworks/ml/nn/runtime/test/specs/V1_1/
H A Dbatch_to_space.mod.py4 output = Output("output", "TENSOR_FLOAT32", "{1, 2, 2, 2}") variable
6 model = model.Operation("BATCH_TO_SPACE_ND", i1, block).To(output)
12 output0 = {output: # output 0
H A Dbatch_to_space_float_1.mod.py4 output = Output("output", "TENSOR_FLOAT32", "{1, 4, 4, 1}") variable
6 model = model.Operation("BATCH_TO_SPACE_ND", i1, block).To(output)
12 output0 = {output: # output 0
H A Dbatch_to_space_float_1_relaxed.mod.py21 output = Output("output", "TENSOR_FLOAT32", "{1, 4, 4, 1}") variable
23 model = model.Operation("BATCH_TO_SPACE_ND", i1, block).To(output)
30 output0 = {output: # output 0
H A Dbatch_to_space_quant8_1.mod.py4 output = Output("output", "TENSOR_QUANT8_ASYMM", "{1, 4, 4, 1}, 1.0, 0") variable
6 model = model.Operation("BATCH_TO_SPACE_ND", i1, block).To(output)
12 output0 = {output: # output 0
H A Dbatch_to_space_relaxed.mod.py20 output = Output("output", "TENSOR_FLOAT32", "{1, 2, 2, 2}") variable
22 model = model.Operation("BATCH_TO_SPACE_ND", i1, block).To(output)
29 output0 = {output: # output 0

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