| /external/valgrind/none/tests/s390x/ |
| bfp-1.c | 7 volatile float f1, f2; variable
31 register float r1 asm("f1") = f1;
37 printf("%f + %f = %f\n", f1, f2, r1);
42 register float r1 asm("f1") = f1;
48 printf("%f - %f = %f\n", f1, f2, r1);
53 register float r1 asm("f1") = f1;
59 printf("%f * %f = %f\n", f1, f2, r1)
[all...] |
| /frameworks/av/media/libstagefright/codecs/amrnb/common/src/ |
| lsp_az.cpp | 94 F1(z) and F2(z), and Lsp_Az, which converts LSP to LPC by multiplying
95 F1(z) by 1+z^(-1) and F2(z) by 1-z^(-1), then calculating A(z) = (F1(z) +
160 This function finds the polynomial F1(z) or F2(z) from the LSPs. If the LSP
161 vector is passed at address 0, F1(z) is computed and if it is passed at
166 F1(z) = product ( 1 - 2 lsp[i] z^-1 + z^-2 )
438 (1) Find the coefficients of F1(z) and F2(z) (see Get_lsp_pol)
439 (2) Multiply F1(z) by 1+z^{-1} and F2(z) by 1-z^{-1}
440 (3) A(z) = ( F1(z) + F2(z) ) / 2
461 Word32 f1[6], f2[6]
517 Word32 f1[6]; local
[all...] |
| /frameworks/av/media/libstagefright/codecs/amrwb/src/ |
| isp_az.cpp | 142 int32 f1[NC16k + 1], f2[NC16k]; local
154 Get_isp_pol_16kHz(&isp[0], f1, nc);
157 f1[i] = shl_int32(f1[i], 2);
167 Get_isp_pol(&isp[0], f1, nc);
181 * Scale F1(z) by (1+isp[m-1]) and F2(z) by (1-isp[m-1])
186 /* f1[i] *= (1.0 + isp[M-1]); */
189 t0 = f1[i];
193 f1[i] += t0;
199 * A(z) = (F1(z)+F2(z))/
[all...] |
| /frameworks/av/media/libstagefright/codecs/amrwbenc/src/ |
| isp_az.c | 47 Word32 f1[NC16k + 1], f2[NC16k]; local
56 Get_isp_pol_16kHz(&isp[0], f1, nc);
59 f1[i] = f1[i] << 2;
62 Get_isp_pol(&isp[0], f1, nc);
84 * Scale F1(z) by (1+isp[m-1]) and F2(z) by (1-isp[m-1]) *
89 /* f1[i] *= (1.0 + isp[M-1]); */
91 hi = f1[i] >> 16;
92 lo = (f1[i] & 0xffff)>>1;
95 f1[i] = vo_L_add(f1[i], t0)
[all...] |
| /frameworks/ml/nn/runtime/test/specs/V1_0/ |
| conv_quant8_2.mod.py | 18 f1 = Parameter("op2", "TENSOR_QUANT8_ASYMM", "{1, 2, 2, 1}, 0.5f, 127", variable
28 model = model.Operation("CONV_2D", i1, f1, b1, pad_valid, stride3,
|
| depthwise_conv2d_float.mod.py | 19 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [.25, 0, .2, 0, .25, 0, 0, .3, .25, 0, 0, 0, .25, .1, 0, 0]) variable
28 i1, f1, b1,
38 # (i1 (conv) f1) + b1
|
| depthwise_conv2d_float_2.mod.py | 19 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [1, 2, 3, 4, -9, 10, -11, 12, 5, 6, 7, 8, 13, -14, 15, -16]) variable
28 i1, f1, b1,
38 # (i1 (depthconv) f1)
|
| depthwise_conv2d_float_large.mod.py | 19 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 2}", [.25, 0, .25, 1, .25, 0, .25, 1]) # depth_out = 2 variable
28 i1, f1, b1,
39 # (i1 (conv) f1) + b1
|
| depthwise_conv2d_float_large_2.mod.py | 19 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [.25, 0, 10, 100, .25, 1, 20, 100, .25, 0, 30, 100, .25, 1, 40, 100]) # depth_out = 4 variable
28 i1, f1, b1,
41 # (i1 (conv) f1) + b1
|
| depthwise_conv2d_float_large_2_weights_as_inputs.mod.py | 19 f1 = Input("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}") # depth_out = 4 variable
28 i1, f1, b1,
40 f1: [
48 # (i1 (conv) f1) + b1
|
| depthwise_conv2d_float_large_weights_as_inputs.mod.py | 19 f1 = Input("op2", "TENSOR_FLOAT32", "{1, 2, 2, 2}") # depth_out = 2 variable
28 i1, f1, b1,
38 f1: [
44 # (i1 (conv) f1) + b1
|
| depthwise_conv2d_float_weights_as_inputs.mod.py | 19 f1 = Input("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}") variable
28 i1, f1, b1,
38 f1:
45 # (i1 (conv) f1) + b1
|
| depthwise_conv2d_quant8.mod.py | 19 f1 = Parameter("op2", "TENSOR_QUANT8_ASYMM", "{1, 2, 2, 2}, 0.5f, 0", [2, 4, 2, 0, 2, 2, 2, 0]) variable
28 i1, f1, b1,
36 # (i1 (depthconv) f1)
|
| depthwise_conv2d_quant8_2.mod.py | 19 f1 = Parameter("op2", "TENSOR_QUANT8_ASYMM", "{1, 2, 2, 4}, 0.5f, 127", [129, 131, 133, 135, 109, 147, 105, 151, 137, 139, 141, 143, 153, 99, 157, 95]) variable
28 i1, f1, b1,
38 # (i1 (depthconv) f1)
|
| depthwise_conv2d_quant8_large.mod.py | 19 f1 = Parameter("op2", "TENSOR_QUANT8_ASYMM", "{1, 2, 2, 2}, 0.5f, 0", [2, 4, 2, 0, 2, 2, 2, 0]) variable
28 i1, f1, b1,
36 # (i1 (depthconv) f1)
|
| depthwise_conv2d_quant8_large_weights_as_inputs.mod.py | 19 f1 = Input("op2", "TENSOR_QUANT8_ASYMM", "{1, 2, 2, 2}, 0.5f, 0") variable
28 i1, f1, b1,
36 f1:
40 # (i1 (depthconv) f1)
|
| depthwise_conv2d_quant8_weights_as_inputs.mod.py | 19 f1 = Input("op2", "TENSOR_QUANT8_ASYMM", "{1, 2, 2, 2}, 0.5f, 0") variable
28 i1, f1, b1,
36 f1:
40 # (i1 (depthconv) f1)
|
| /frameworks/ml/nn/runtime/test/specs/V1_1/ |
| depthwise_conv2d_float_2_relaxed.mod.py | 19 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [1, 2, 3, 4, -9, 10, -11, 12, 5, 6, 7, 8, 13, -14, 15, -16]) variable
28 i1, f1, b1,
39 # (i1 (depthconv) f1)
|
| depthwise_conv2d_float_large_2_relaxed.mod.py | 19 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [.25, 0, 10, 100, .25, 1, 20, 100, .25, 0, 30, 100, .25, 1, 40, 100]) # depth_out = 4 variable
28 i1, f1, b1,
42 # (i1 (conv) f1) + b1
|
| depthwise_conv2d_float_large_2_weights_as_inputs_relaxed.mod.py | 19 f1 = Input("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}") # depth_out = 4 variable
28 i1, f1, b1,
41 f1: [
49 # (i1 (conv) f1) + b1
|
| depthwise_conv2d_float_large_relaxed.mod.py | 19 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 2}", [.25, 0, .25, 1, .25, 0, .25, 1]) # depth_out = 2 variable
28 i1, f1, b1,
40 # (i1 (conv) f1) + b1
|
| depthwise_conv2d_float_large_weights_as_inputs_relaxed.mod.py | 19 f1 = Input("op2", "TENSOR_FLOAT32", "{1, 2, 2, 2}") # depth_out = 2 variable
28 i1, f1, b1,
39 f1: [
45 # (i1 (conv) f1) + b1
|
| depthwise_conv2d_float_relaxed.mod.py | 19 f1 = Parameter("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}", [.25, 0, .2, 0, .25, 0, 0, .3, .25, 0, 0, 0, .25, .1, 0, 0]) variable
28 i1, f1, b1,
39 # (i1 (conv) f1) + b1
|
| depthwise_conv2d_float_weights_as_inputs_relaxed.mod.py | 19 f1 = Input("op2", "TENSOR_FLOAT32", "{1, 2, 2, 4}") variable
28 i1, f1, b1,
39 f1:
46 # (i1 (conv) f1) + b1
|
| /prebuilts/go/darwin-x86/src/cmd/compile/internal/gc/testdata/ |
| namedReturn.go | 27 func f1() (t T1) { func
82 if v := f1()[0][1]; v != 92 {
83 fmt.Printf("f1()[0][1]=%d, want 92\n", v)
|
