更新libclamav库1.0.0版本

clamav/libclamav_rust/.cargo/vendor/rustfft/tools/gen_sse_butterflies.py

@@ -0,0 +1,178 @@
+# A simple Python script to generate the code for odd-sized optimized DFTs
+# The generated code is simply printed in the terminal.
+# This is only intended for prime lengths, where the usual tricks can't be used.
+# The generated code is O(n^2), but for short lengths this is still faster than fancier algorithms.
+# Example, make a length 5 Dft:
+# > python genbutterflies.py 5
+# Output:
+# let x14p = *buffer.get_unchecked(1) + *buffer.get_unchecked(4);
+# let x14n = *buffer.get_unchecked(1) - *buffer.get_unchecked(4);
+# let x23p = *buffer.get_unchecked(2) + *buffer.get_unchecked(3);
+# let x23n = *buffer.get_unchecked(2) - *buffer.get_unchecked(3);
+# let sum = *buffer.get_unchecked(0) + x14p + x23p;
+# let b14re_a = buffer.get_unchecked(0).re + self.twiddle1.re*x14p.re + self.twiddle2.re*x23p.re;
+# let b14re_b = self.twiddle1.im*x14n.im + self.twiddle2.im*x23n.im;
+# let b23re_a = buffer.get_unchecked(0).re + self.twiddle2.re*x14p.re + self.twiddle1.re*x23p.re;
+# let b23re_b = self.twiddle2.im*x14n.im + -self.twiddle1.im*x23n.im;
+# 
+# let b14im_a = buffer.get_unchecked(0).im + self.twiddle1.re*x14p.im + self.twiddle2.re*x23p.im;
+# let b14im_b = self.twiddle1.im*x14n.re + self.twiddle2.im*x23n.re;
+# let b23im_a = buffer.get_unchecked(0).im + self.twiddle2.re*x14p.im + self.twiddle1.re*x23p.im;
+# let b23im_b = self.twiddle2.im*x14n.re + -self.twiddle1.im*x23n.re;
+# 
+# let out1re = b14re_a - b14re_b;
+# let out1im = b14im_a + b14im_b;
+# let out2re = b23re_a - b23re_b;
+# let out2im = b23im_a + b23im_b;
+# let out3re = b23re_a + b23re_b;
+# let out3im = b23im_a - b23im_b;
+# let out4re = b14re_a + b14re_b;
+# let out4im = b14im_a - b14im_b;
+# *buffer.get_unchecked_mut(0) = sum;
+# *buffer.get_unchecked_mut(1) = Complex{ re: out1re, im: out1im };
+# *buffer.get_unchecked_mut(2) = Complex{ re: out2re, im: out2im };
+# *buffer.get_unchecked_mut(3) = Complex{ re: out3re, im: out3im };
+# *buffer.get_unchecked_mut(4) = Complex{ re: out4re, im: out4im };
+#
+#
+# This required the Butterfly5 to already exist, with twiddles defined like this:
+# pub struct Butterfly5<T> {
+#     twiddle1: Complex<T>,
+#     twiddle2: Complex<T>,
+# 	direction: FftDirection,
+# }
+# 
+# With twiddle values:
+# twiddle1: Complex<T> = twiddles::single_twiddle(1, 5, direction);
+# twiddle2: Complex<T> = twiddles::single_twiddle(2, 5, direction);
+
+import sys
+
+def make_shuffling_single_f64(len):
+    inputs =  ", ".join([str(n) for n in range(len)])
+    print(f"let values = read_complex_to_array!(input, {{{inputs}}});")
+    print("")
+    print("let out = self.perform_fft_direct(values);")
+    print("")
+    print(f"write_complex_to_array!(out, output, {{{inputs}}});")
+
+def make_shuffling_single_f32(len):
+    inputs =  ", ".join([str(n) for n in range(len)])
+    print(f"let values = read_partial1_complex_to_array!(input, {{{inputs}}});")
+    print("")
+    print("let out = self.perform_parallel_fft_direct(values);")
+    print("")
+    print(f"write_partial_lo_complex_to_array!(out, output, {{{inputs}}});")
+
+
+def make_shuffling_parallel_f32(len):
+    inputs =  ", ".join([str(2*n) for n in range(len)])
+    outputs =  ", ".join([str(n) for n in range(len)])
+    print(f"let input_packed = read_complex_to_array!(input, {{{inputs}}});")
+    print("")
+    print("let values = [")
+    for n in range(int(len/2)):
+        print(f"    extract_lo_hi_f32(input_packed[{int(n)}], input_packed[{int(len/2 + n)}]),")
+        print(f"    extract_hi_lo_f32(input_packed[{int(n)}], input_packed[{int(len/2 + n+1)}]),")
+    print(f"    extract_lo_hi_f32(input_packed[{int(len/2)}], input_packed[{int(len-1)}]),")
+    print("];")
+    print("")
+    print("let out = self.perform_parallel_fft_direct(values);")
+    print("")
+    print("let out_packed = [")
+    for n in range(int(len/2)):
+        print(f"    extract_lo_lo_f32(out[{int(2*n)}], out[{int(2*n+1)}]),")
+    print(f"    extract_lo_hi_f32(out[{int(len-1)}], out[0]),")
+    for n in range(int(len/2)):
+        print(f"    extract_hi_hi_f32(out[{int(2*n+1)}], out[{int(2*n+2)}]),")
+    print("];")
+    print("")
+    print(f"write_complex_to_array_strided!(out_packed, output, 2, {{{outputs}}});")
+
+
+def make_butterfly(len, fft2func, calcfunc, mulfunc, rotatefunc):
+
+
+    halflen = int((fftlen+1)/2)
+
+    for n in range(1, halflen):
+        print(f"let [x{n}p{fftlen-n}, x{n}m{fftlen-n}] = {fft2func}(values[{n}], values[{fftlen-n}]);")
+
+
+
+    print("")
+    items = []
+    for m in range (1, halflen):
+        for n in range(1, halflen):
+            mn = (m*n)%fftlen
+            if mn > fftlen/2:
+                mn = fftlen-mn
+            print(f"let t_a{m}_{n} = {mulfunc}(self.twiddle{mn}re, x{n}p{fftlen-n});")
+
+    print("")
+    items = []
+    for m in range (1, halflen):
+        for n in range(1, halflen):
+            mn = (m*n)%fftlen
+            if mn > fftlen/2:
+                mn = fftlen-mn
+            print(f"let t_b{m}_{n} = {mulfunc}(self.twiddle{mn}im, x{n}m{fftlen-n});")
+            
+
+    print("")
+    print("let x0 = values[0];")
+    for m in range(1, halflen):
+        items = ["x0"]
+        for n in range(1, halflen):
+            items.append(f"t_a{m}_{n}")
+        terms = " + ".join(items)
+        print(f'let t_a{m} = {calcfunc}({terms});')
+
+
+    print("")
+    for m in range(1, halflen):
+        terms = f"t_b{m}_1"
+        for n in range(2, halflen):
+            mn = (m*n)%fftlen
+            if mn > fftlen/2:
+                sign = " - "
+            else:
+                sign = " + "
+            terms = terms + sign + f"t_b{m}_{n}"
+        print(f'let t_b{m} = {calcfunc}({terms});')
+
+    print("")
+    for m in range(1, halflen):
+        print(f'let t_b{m}_rot = self.rotate.{rotatefunc}(t_b{m});')
+
+    print("")
+    items = ["x0"]
+    for n in range(1, halflen):
+        items.append(f"x{n}p{fftlen-n}")
+    terms = " + ".join(items)
+    print(f'let y0 = {calcfunc}({terms});')
+
+    for m in range(1, halflen):
+        print(f"let [y{m}, y{fftlen-m}] = {fft2func}(t_a{m}, t_b{m}_rot);")
+
+    items = []
+    for n in range(0, fftlen):
+        items.append(f"y{n}")
+    print(f'[{", ".join(items)}]')
+
+
+if __name__ == "__main__":
+    fftlen = int(sys.argv[1])
+    print("\n\n--------------- f32 ---------------")
+    print("\n ----- perform_fft_contiguous -----")
+    make_shuffling_single_f32(fftlen)
+    print("\n ----- perform_parallel_fft_contiguous -----")
+    make_shuffling_parallel_f32(fftlen)
+    print("\n ----- perform_parallel_fft_direct -----")
+    make_butterfly(fftlen, "parallel_fft2_interleaved_f32", "calc_f32!", "_mm_mul_ps", "rotate_both")
+
+    print("\n\n--------------- f64 ---------------")
+    print("\n ----- perform_fft_contiguous -----")
+    make_shuffling_single_f64(fftlen)
+    print("\n ----- perform_parallel_fft_direct -----")
+    make_butterfly(fftlen, "solo_fft2_f64", "calc_f64!", "_mm_mul_pd", "rotate")

clamav/libclamav_rust/.cargo/vendor/rustfft/tools/genbutterflies.py

@@ -0,0 +1,115 @@
+# A simple Python script to generate the code for odd-sized optimized DFTs
+# The generated code is simply printed in the terminal.
+# This is only intended for prime lengths, where the usual tricks can't be used.
+# The generated code is O(n^2), but for short lengths this is still faster than fancier algorithms.
+# Example, make a length 5 Dft:
+# > python genbutterflies.py 5
+# Output:
+# let x14p = *buffer.get_unchecked(1) + *buffer.get_unchecked(4);
+# let x14n = *buffer.get_unchecked(1) - *buffer.get_unchecked(4);
+# let x23p = *buffer.get_unchecked(2) + *buffer.get_unchecked(3);
+# let x23n = *buffer.get_unchecked(2) - *buffer.get_unchecked(3);
+# let sum = *buffer.get_unchecked(0) + x14p + x23p;
+# let b14re_a = buffer.get_unchecked(0).re + self.twiddle1.re*x14p.re + self.twiddle2.re*x23p.re;
+# let b14re_b = self.twiddle1.im*x14n.im + self.twiddle2.im*x23n.im;
+# let b23re_a = buffer.get_unchecked(0).re + self.twiddle2.re*x14p.re + self.twiddle1.re*x23p.re;
+# let b23re_b = self.twiddle2.im*x14n.im + -self.twiddle1.im*x23n.im;
+# 
+# let b14im_a = buffer.get_unchecked(0).im + self.twiddle1.re*x14p.im + self.twiddle2.re*x23p.im;
+# let b14im_b = self.twiddle1.im*x14n.re + self.twiddle2.im*x23n.re;
+# let b23im_a = buffer.get_unchecked(0).im + self.twiddle2.re*x14p.im + self.twiddle1.re*x23p.im;
+# let b23im_b = self.twiddle2.im*x14n.re + -self.twiddle1.im*x23n.re;
+# 
+# let out1re = b14re_a - b14re_b;
+# let out1im = b14im_a + b14im_b;
+# let out2re = b23re_a - b23re_b;
+# let out2im = b23im_a + b23im_b;
+# let out3re = b23re_a + b23re_b;
+# let out3im = b23im_a - b23im_b;
+# let out4re = b14re_a + b14re_b;
+# let out4im = b14im_a - b14im_b;
+# *buffer.get_unchecked_mut(0) = sum;
+# *buffer.get_unchecked_mut(1) = Complex{ re: out1re, im: out1im };
+# *buffer.get_unchecked_mut(2) = Complex{ re: out2re, im: out2im };
+# *buffer.get_unchecked_mut(3) = Complex{ re: out3re, im: out3im };
+# *buffer.get_unchecked_mut(4) = Complex{ re: out4re, im: out4im };
+#
+#
+# This required the Butterfly5 to already exist, with twiddles defined like this:
+# pub struct Butterfly5<T> {
+#     twiddle1: Complex<T>,
+#     twiddle2: Complex<T>,
+# 	direction: FftDirection,
+# }
+# 
+# With twiddle values:
+# twiddle1: Complex<T> = twiddles::single_twiddle(1, 5, direction);
+# twiddle2: Complex<T> = twiddles::single_twiddle(2, 5, direction);
+
+import sys
+
+len = int(sys.argv[1])
+
+halflen = int((len+1)/2)
+
+for n in range(1, halflen):
+    print(f"let x{n}{len-n}p = *buffer.get_unchecked({n}) + *buffer.get_unchecked({len-n});")
+    print(f"let x{n}{len-n}n = *buffer.get_unchecked({n}) - *buffer.get_unchecked({len-n});")
+
+row = ["let sum = *buffer.get_unchecked(0)"]
+for n in range(1, halflen):
+    row.append(f"x{n}{len-n}p")
+print(" + ".join(row) + ";")
+
+for n in range(1, halflen):
+    row = [f"let b{n}{len-n}re_a = buffer.get_unchecked(0).re"]
+    for m in range(1, halflen):
+        mn = (m*n)%len
+        if mn > len/2:
+            mn = len-mn
+        row.append(f"self.twiddle{mn}.re*x{m}{len-m}p.re")
+    print(" + ".join(row) + ";")
+    row = []
+    for m in range(1, halflen):
+        mn = (m*n)%len
+        if mn > len/2:
+            mn = len-mn
+            row.append(f"-self.twiddle{mn}.im*x{m}{len-m}n.im")
+        else:
+            row.append(f"self.twiddle{mn}.im*x{m}{len-m}n.im")
+    print(f"let b{n}{len-n}re_b = " + " + ".join(row) + ";")
+print("")
+
+for n in range(1, halflen):
+    row = [f"let b{n}{len-n}im_a = buffer.get_unchecked(0).im"]
+    for m in range(1, halflen):
+        mn = (m*n)%len
+        if mn > len/2:
+            mn = len-mn
+        row.append(f"self.twiddle{mn}.re*x{m}{len-m}p.im")
+    print(" + ".join(row) + ";")
+    row = []
+    for m in range(1, halflen):
+        mn = (m*n)%len
+        if mn > len/2:
+            mn = len-mn
+            row.append(f"-self.twiddle{mn}.im*x{m}{len-m}n.re")
+        else:
+            row.append(f"self.twiddle{mn}.im*x{m}{len-m}n.re")
+    print(f"let b{n}{len-n}im_b = " + " + ".join(row) + ";")
+print("")
+
+for n in range(1,len):
+    nfold = n
+    sign_re = "-"
+    sign_im = "+"
+    if n > len/2:
+        nfold = len-n
+        sign_re = "+"
+        sign_im = "-"
+    print(f"let out{n}re = b{nfold}{len-nfold}re_a {sign_re} b{nfold}{len-nfold}re_b;")
+    print(f"let out{n}im = b{nfold}{len-nfold}im_a {sign_im} b{nfold}{len-nfold}im_b;")
+
+print("*buffer.get_unchecked_mut(0) = sum;")
+for n in range(1,len):
+    print(f"*buffer.get_unchecked_mut({n}) = Complex{{ re: out{n}re, im: out{n}im }};")

clamav/libclamav_rust/.cargo/vendor/rustfft/tools/p2comparison.py

@@ -0,0 +1,65 @@
+import sys
+import math
+from matplotlib import pyplot as plt
+
+
+with open(sys.argv[1]) as f:
+    lines = f.readlines()
+
+results = {"f32": {"scalar": {}, "sse": {}, "avx":{}}, "f64": {"scalar": {}, "sse": {}, "avx":{}}}
+
+for line in lines:
+    if line.startswith("test ") and not line.startswith("test result"):
+        name, result = line.split("... bench:")
+        name = name.split()[1]
+        _, length, ftype, algo = name.split("_")
+        value = float(result.strip().split(" ")[0].replace(",", ""))
+        results[ftype][algo][float(length)] = value
+
+lengths = sorted(list(results["f32"]["scalar"].keys()))
+
+
+scalar_32 = []
+avx_32 = []
+sse_32 = []
+for l in lengths:
+    sc32 = results["f32"]["scalar"][l]
+    av32 = results["f32"]["avx"][l]
+    ss32 = results["f32"]["sse"][l]
+    scalar_32.append(100.0)
+    sse_32.append(100.0 * sc32/ss32)
+    avx_32.append(100.0 * sc32/av32)
+
+scalar_64 = []
+avx_64 = []
+sse_64 = []
+for l in lengths:
+    sc64 = results["f64"]["scalar"][l]
+    av64 = results["f64"]["avx"][l]
+    ss64 = results["f64"]["sse"][l]
+    scalar_64.append(100.0)
+    sse_64.append(100.0 * sc64/ss64)
+    avx_64.append(100.0 * sc64/av64)
+
+lengths = [math.log(l, 2) for l in lengths]
+
+plt.figure()
+plt.plot(lengths, scalar_64, lengths, sse_64, lengths, avx_64)
+plt.title("f64")
+plt.ylabel("relative speed, %")
+plt.xlabel("log2(length)")
+plt.xticks(list(range(4,23)))
+plt.grid()
+plt.legend(["scalar", "sse", "avx"])
+
+plt.figure()
+plt.plot(lengths, scalar_32, lengths, sse_32, lengths, avx_32)
+plt.title("f32")
+plt.ylabel("relative speed, %")
+plt.xlabel("log2(length)")
+plt.legend(["scalar", "sse", "avx"])
+plt.xticks(list(range(4,23)))
+plt.grid()
+plt.show()
+
+

clamav/libclamav_rust/.cargo/vendor/rustfft/tools/p2comparison_neon.py

@@ -0,0 +1,59 @@
+import sys
+import math
+from matplotlib import pyplot as plt
+
+
+with open(sys.argv[1]) as f:
+    lines = f.readlines()
+
+results = {"f32": {"scalar": {}, "neon": {}}, "f64": {"scalar": {}, "neon": {}}}
+
+for line in lines:
+    if line.startswith("test ") and not line.startswith("test result"):
+        name, result = line.split("... bench:")
+        name = name.split()[1]
+        _, length, ftype, algo = name.split("_")
+        value = float(result.strip().split(" ")[0].replace(",", ""))
+        results[ftype][algo][float(length)] = value
+
+lengths = sorted(list(results["f32"]["scalar"].keys()))
+
+
+scalar_32 = []
+neon_32 = []
+for l in lengths:
+    sc32 = results["f32"]["scalar"][l]
+    nn32 = results["f32"]["neon"][l]
+    scalar_32.append(100.0)
+    neon_32.append(100.0 * sc32/nn32)
+
+scalar_64 = []
+neon_64 = []
+for l in lengths:
+    sc64 = results["f64"]["scalar"][l]
+    nn64 = results["f64"]["neon"][l]
+    scalar_64.append(100.0)
+    neon_64.append(100.0 * sc64/nn64)
+
+lengths = [math.log(l, 2) for l in lengths]
+
+plt.figure()
+plt.plot(lengths, scalar_64, lengths, neon_64)
+plt.title("f64")
+plt.ylabel("relative speed, %")
+plt.xlabel("log2(length)")
+plt.xticks(list(range(4,23)))
+plt.grid()
+plt.legend(["scalar", "neon"])
+
+plt.figure()
+plt.plot(lengths, scalar_32, lengths, neon_32)
+plt.title("f32")
+plt.ylabel("relative speed, %")
+plt.xlabel("log2(length)")
+plt.legend(["scalar", "neon"])
+plt.xticks(list(range(4,23)))
+plt.grid()
+plt.show()
+
+