Merge branch 'TimDettmers:main' into memory-efficient-backward

9 files changed, 125 insertions, 129 deletions

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 1017721..40467dc 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -90,3 +90,19 @@ Features:
 Bug fixes:
  - Now throws and error if LLM.int8() is used on a GPU that is not supported.
  - Enhances error messaging if CUDA SETUP fails.
+
+
+### 0.33.0
+
+#### Various bug fixes
+
+Features:
+ - CPU quantization now supports a variable `blocksize` variable to enhance quantization speed or precision.
+
+Bug fixes:
+ - fixed an issue in CPU quantization where tensors with more than 2^31 elements would fail 19a7adca7a6c9bf7061a384d7e9d9b13676a1a88
+ - fixed a bug where cpu binaries would fail if no GPU would be detected eab4d8232d558f2e6bd7f7cc3d00e2e6e94f4e80
+ - fixed an issue where cpu binaries cause additional stdout messages 92a3363096e10ad6a5c4e944af898bd1186d806a
+ - fixed an import of bnb.utils 2e630b55f51d454f3bd723dffda68a07ef93190c
+
+We thank @mryab, @mbrukman, @chessgecko, @dbaranchuk for pull request with bug fixes and new features.
diff --git a/bitsandbytes/functional.py b/bitsandbytes/functional.py
index 22200f2..c104ebd 100644
--- a/bitsandbytes/functional.py
+++ b/bitsandbytes/functional.py
@@ -369,13 +369,7 @@ def estimate_quantiles(
     return out
 
 
-def quantize_blockwise(
-    A: Tensor,
-    code: Tensor = None,
-    absmax: Tensor = None,
-    rand=None,
-    out: Tensor = None,
-) -> Tensor:
+def quantize_blockwise(A: Tensor, code: Tensor = None, absmax: Tensor = None, rand=None, out: Tensor = None, blocksize=4096) -> Tensor:
     """
     Quantize tensor A in blocks of size 4096 values.
 
@@ -412,9 +406,9 @@ def quantize_blockwise(
 
     if absmax is None:
         n = A.numel()
-        num_blocks = 4096
-        blocks = n // num_blocks
-        blocks += 1 if n % num_blocks > 0 else 0
+        blocksize = (blocksize if A.device.type == 'cpu' else 4096)
+        blocks = n // blocksize
+        blocks += 1 if n % blocksize > 0 else 0
         absmax = torch.zeros((blocks,), device=A.device)
 
     if out is None:
@@ -426,46 +420,18 @@ def quantize_blockwise(
             assert rand.numel() >= 1024
             rand_offset = random.randint(0, 1023)
             if A.dtype == torch.float32:
-                lib.cquantize_blockwise_stochastic_fp32(
-                    get_ptr(code),
-                    get_ptr(A),
-                    get_ptr(absmax),
-                    get_ptr(out),
-                    get_ptr(rand),
-                    ct.c_int32(rand_offset),
-                    ct.c_int(A.numel()),
-                )
+                lib.cquantize_blockwise_stochastic_fp32(get_ptr(code), get_ptr(A),get_ptr(absmax), get_ptr(out), get_ptr(rand), ct.c_int32(rand_offset), ct.c_int(A.numel()))
             elif A.dtype == torch.float16:
-                lib.cquantize_blockwise_stochastic_fp16(
-                    get_ptr(code),
-                    get_ptr(A),
-                    get_ptr(absmax),
-                    get_ptr(out),
-                    get_ptr(rand),
-                    ct.c_int32(rand_offset),
-                    ct.c_int(A.numel()),
-                )
+                lib.cquantize_blockwise_stochastic_fp16(get_ptr(code), get_ptr(A),get_ptr(absmax), get_ptr(out), get_ptr(rand), ct.c_int32(rand_offset), ct.c_int(A.numel()))
             else:
                 raise ValueError(
                     f"Blockwise quantization only supports 16/32-bit floats, but got {A.dtype}"
                 )
         else:
             if A.dtype == torch.float32:
-                lib.cquantize_blockwise_fp32(
-                    get_ptr(code),
-                    get_ptr(A),
-                    get_ptr(absmax),
-                    get_ptr(out),
-                    ct.c_int(A.numel()),
-                )
+                lib.cquantize_blockwise_fp32(get_ptr(code), get_ptr(A), get_ptr(absmax), get_ptr(out),ct.c_int(A.numel()))
             elif A.dtype == torch.float16:
-                lib.cquantize_blockwise_fp16(
-                    get_ptr(code),
-                    get_ptr(A),
-                    get_ptr(absmax),
-                    get_ptr(out),
-                    ct.c_int(A.numel()),
-                )
+                lib.cquantize_blockwise_fp16(get_ptr(code), get_ptr(A), get_ptr(absmax), get_ptr(out),ct.c_int(A.numel()))
             else:
                 raise ValueError(
                     f"Blockwise quantization only supports 16/32-bit floats, but got {A.dtype}"
@@ -473,13 +439,7 @@ def quantize_blockwise(
     else:
         # cpu
         assert rand is None
-        lib.cquantize_blockwise_cpu_fp32(
-            get_ptr(code),
-            get_ptr(A),
-            get_ptr(absmax),
-            get_ptr(out),
-            ct.c_int(A.numel()),
-        )
+        lib.cquantize_blockwise_cpu_fp32(get_ptr(code), get_ptr(A), get_ptr(absmax), get_ptr(out), ct.c_longlong(blocksize), ct.c_longlong(A.numel()))
 
     return out, (absmax, code)
 
@@ -529,43 +489,21 @@ def dequantize_blockwise(
     if quant_state is None:
         quant_state = (absmax, code)
 
-    if blocksize not in [2048, 4096]:
-        raise ValueError(
-            f"The blockwise of {blocksize} is not supported. Supported values: [2048 4096]"
-        )
 
     if A.device.type != 'cpu':
+        if blocksize not in [2048, 4096]:
+            raise ValueError(f"The blockwise of {blocksize} is not supported. Supported values: [2048 4096]")
         is_on_gpu([A, out])
         if out.dtype == torch.float32:
-            lib.cdequantize_blockwise_fp32(
-                get_ptr(quant_state[1]),
-                get_ptr(A),
-                get_ptr(quant_state[0]),
-                get_ptr(out),
-                ct.c_int(blocksize),
-                ct.c_int(A.numel()),
-            )
+            lib.cdequantize_blockwise_fp32(get_ptr(quant_state[1]), get_ptr(A), get_ptr(quant_state[0]), get_ptr(out), ct.c_int(blocksize), ct.c_int(A.numel()))
         elif out.dtype == torch.float16:
-            lib.cdequantize_blockwise_fp16(
-                get_ptr(quant_state[1]),
-                get_ptr(A),
-                get_ptr(quant_state[0]),
-                get_ptr(out),
-                ct.c_int(blocksize),
-                ct.c_int(A.numel()),
-            )
+            lib.cdequantize_blockwise_fp16(get_ptr(quant_state[1]), get_ptr(A), get_ptr(quant_state[0]), get_ptr(out), ct.c_int(blocksize), ct.c_int(A.numel()))
         else:
             raise ValueError(
                 f"Blockwise quantization only supports 16/32-bit floats, but got {A.dtype}"
             )
     else:
-        lib.cdequantize_blockwise_cpu_fp32(
-            get_ptr(quant_state[1]),
-            get_ptr(A),
-            get_ptr(quant_state[0]),
-            get_ptr(out),
-            ct.c_int(A.numel()),
-        )
+        lib.cdequantize_blockwise_cpu_fp32(get_ptr(quant_state[1]), get_ptr(A), get_ptr(quant_state[0]), get_ptr(out), ct.c_longlong(blocksize), ct.c_longlong(A.numel()))
 
     return out
 
diff --git a/csrc/common.cpp b/csrc/common.cpp
index 972602b..52f0299 100644
--- a/csrc/common.cpp
+++ b/csrc/common.cpp
@@ -12,16 +12,16 @@ void *quantize_block(void *arguments) {
 
     // 1. find absmax in block
     float absmax_block = -FLT_MAX;
-    for (int i = args->block_idx; i < args->block_end; i++)
+    for (long long i = args->block_idx; i < args->block_end; i++)
         absmax_block = fmax(absmax_block, fabs(args->A[i]));
 
-    args->absmax[args->block_idx / BLOCK_SIZE] = absmax_block;
+    args->absmax[args->block_idx / args->blocksize] = absmax_block;
 
-    for (int i = args->block_idx; i < args->block_end; i++) {
+    for (long long i = args->block_idx; i < args->block_end; i++) {
         // 2. divide input value by absmax to normalize into [-1.0, 1.0]
         // 3. do binary search to find the closest value
         float normed_value = args->A[i] / absmax_block;
-        int idx = args->bin_searcher->scalar(normed_value);
+        long long idx = args->bin_searcher->scalar(normed_value);
 
         // 4. check minimal distance
         // The binary search returns always the value to the left, which might not be the closest value
diff --git a/csrc/common.h b/csrc/common.h
index 2f25a58..c99034e 100644
--- a/csrc/common.h
+++ b/csrc/common.h
@@ -5,18 +5,20 @@
 
 using namespace BinSearch;
 
+#define BLOCK_SIZE 16384
+
 struct quantize_block_args {
     BinAlgo<Scalar, float, Direct2> *bin_searcher;
     float *code;
     float *A;
     float *absmax;
     unsigned char *out;
-    int block_end;
-    int block_idx;
-    int threadidx;
+    long long block_end;
+    long long block_idx;
+    long long threadidx;
+		long long blocksize;
 };
 
-#define BLOCK_SIZE 4096
 
 void *quantize_block(void *arguments);
 
diff --git a/csrc/cpu_ops.cpp b/csrc/cpu_ops.cpp
index 89de52d..2081e68 100644
--- a/csrc/cpu_ops.cpp
+++ b/csrc/cpu_ops.cpp
@@ -4,54 +4,70 @@
 
 using namespace BinSearch;
 
-void dequantize_cpu(float *code, unsigned char *A, float *absmax, float *out, int n) {
-    for (int block_idx = 0; block_idx < n; block_idx += BLOCK_SIZE) {
-        int valid_items = n - block_idx >= BLOCK_SIZE ? BLOCK_SIZE : n - block_idx;
-        int block_end = block_idx + valid_items;
-        for (int i = block_idx; i < block_end; i++)
-            out[i] = code[A[i]] * absmax[block_idx / BLOCK_SIZE];
+void dequantize_cpu(float *code, unsigned char *A, float *absmax, float *out, long long blocksize, long long n) {
+    for (long long block_idx = 0; block_idx < n; block_idx += blocksize) {
+        long long valid_items = n - block_idx >= blocksize ? blocksize : n - block_idx;
+        long long block_end = block_idx + valid_items;
+        for (long long i = block_idx; i < block_end; i++)
+            out[i] = code[A[i]] * absmax[block_idx / blocksize];
     }
 }
 
-void quantize_cpu(float *code, float *A, float *absmax, unsigned char *out, int n) {
+void quantize_cpu(float *code, float *A, float *absmax, unsigned char *out, long long blocksize, long long n)
+{
 
     // the default code is has range [-0.993, 1.0] which can cause an error in the binary search algorithm used below
     code[0] = -1.0f;
 
-    int num_blocks = n / BLOCK_SIZE;
-    num_blocks += n % BLOCK_SIZE == 0 ? 0 : 1;
-
-    pthread_t *threads = (pthread_t *) malloc(sizeof(pthread_t) * num_blocks);
-    struct quantize_block_args **args = (quantize_block_args **) malloc(num_blocks * sizeof(quantize_block_args *));
-
-    for (int i = 0; i < num_blocks; i++)
-        args[i] = (quantize_block_args *) malloc(sizeof(quantize_block_args));
+    long long num_blocks = n / blocksize;
+    num_blocks += n % blocksize == 0 ? 0 : 1;
 
     const uint32 elements_code = 256;
     BinAlgo<Scalar, float, Direct2> bin_searcher(code, elements_code);
 
-    for (int block_idx = 0; block_idx < n; block_idx += BLOCK_SIZE) {
-        int valid_items = n - block_idx >= BLOCK_SIZE ? BLOCK_SIZE : n - block_idx;
-        int block_end = block_idx + valid_items;
-
-        struct quantize_block_args *arg = args[block_idx / BLOCK_SIZE];
-        arg->bin_searcher = &bin_searcher;
-        arg->code = code;
-        arg->A = A;
-        arg->absmax = absmax;
-        arg->out = out;
-        arg->block_end = block_end;
-        arg->block_idx = block_idx;
-        arg->threadidx = block_idx / BLOCK_SIZE;
-
-        pthread_create(&threads[block_idx / BLOCK_SIZE], NULL, &quantize_block, (void *) arg);
-    }
+    int thread_wave_size = 256;
+    // we chunk the thresds into waves of 256 since the max limit is
+    // between 16k and 64k on Linux (we reach this when running BLOOM-176B with a large batch size)
+    for(long long offset = 0; offset < num_blocks; offset+=thread_wave_size)
+    {
+      long long valid_chunks = num_blocks - offset >= thread_wave_size ? thread_wave_size : num_blocks - offset;
+      pthread_t *threads = (pthread_t *) malloc(sizeof(pthread_t) * valid_chunks);
+
+      struct quantize_block_args **args = (quantize_block_args **) malloc(valid_chunks * sizeof(quantize_block_args *));
+
+      for(long long i = 0; i < valid_chunks; i++)
+          args[i] = (quantize_block_args *) malloc(sizeof(quantize_block_args));
 
-    for (int i = 0; i < num_blocks; i++)
-        int err = pthread_join(threads[i], NULL);
+      int chunks_processed = 0;
+      for(long long block_idx = offset*blocksize; block_idx < n; block_idx += blocksize)
+      {
+          long long valid_items = n - block_idx >= blocksize ? blocksize : n - block_idx;
+          long long block_end = block_idx + valid_items;
+
+          struct quantize_block_args *arg = args[chunks_processed];
+          arg->bin_searcher = &bin_searcher;
+          arg->code = code;
+          arg->A = A;
+          arg->absmax = absmax;
+          arg->out = out;
+          arg->block_end = block_end;
+          arg->block_idx = block_idx;
+          arg->threadidx = block_idx / blocksize;
+          arg->blocksize = blocksize;
+
+          pthread_create(&threads[chunks_processed], NULL, &quantize_block, (void *) arg);
+          chunks_processed += 1;
+          if(chunks_processed == valid_chunks){ break; }
+      }
+
+      for (int i = 0; i < valid_chunks; i++)
+          int err = pthread_join(threads[i], NULL);
+      
+      free(threads);
+      for (int i = 0; i < valid_chunks; i++)
+          free(args[i]);
+      free(args);
+
+    }
 
-    free(threads);
-    for (int i = 0; i < num_blocks; i++)
-        free(args[i]);
-    free(args);
 }
diff --git a/csrc/cpu_ops.h b/csrc/cpu_ops.h
index 57145a9..2ddf81e 100644
--- a/csrc/cpu_ops.h
+++ b/csrc/cpu_ops.h
@@ -1,9 +1,10 @@
 #ifndef BITSANDBYTES_CPU_OPS_H
 #define BITSANDBYTES_CPU_OPS_H
 
+#include <iostream>
+#include <stdio.h>
 
-void quantize_cpu(float *code, float *A, float *absmax, unsigned char *out, int n);
-
-void dequantize_cpu(float *code, unsigned char *A, float *absmax, float *out, int n);
+void quantize_cpu(float *code, float *A, float *absmax, unsigned char *out, long long blocksize, long long n);
+void dequantize_cpu(float *code, unsigned char *A, float *absmax, float *out, long long blocksize, long long n);
 
 #endif
diff --git a/csrc/pythonInterface.c b/csrc/pythonInterface.c
index 0707674..58e26a9 100644
--- a/csrc/pythonInterface.c
+++ b/csrc/pythonInterface.c
@@ -287,7 +287,7 @@ extern "C"
 	void cextractOutliers_ampere(char * A, int *idx, char *out, int idx_size, int rows, int cols){ extractOutliers_ampere(A, idx, out, idx_size, rows, cols); }
 
 #endif
-	void cquantize_blockwise_cpu_fp32(float *code, float *A, float *absmax, unsigned char *out, const int n){ quantize_cpu(code, A, absmax, out, n); }
-	void cdequantize_blockwise_cpu_fp32(float *code, unsigned char *A, float *absmax, float *out, const int n){ dequantize_cpu(code, A, absmax, out, n); }
+	void cquantize_blockwise_cpu_fp32(float *code, float *A, float *absmax, unsigned char *out, long long blocksize, long long n){ quantize_cpu(code, A, absmax, out, blocksize, n); }
+	void cdequantize_blockwise_cpu_fp32(float *code, unsigned char *A, float *absmax, float *out, long long blocksize, long long n){ dequantize_cpu(code, A, absmax, out, blocksize, n); }
 }
 
diff --git a/setup.py b/setup.py
index b722ae9..97b99d0 100644
--- a/setup.py
+++ b/setup.py
@@ -18,7 +18,7 @@ def read(fname):
 
 setup(
     name=f"bitsandbytes",
-    version=f"0.32.3",
+    version=f"0.33.1",
     author="Tim Dettmers",
     author_email="dettmers@cs.washington.edu",
     description="8-bit optimizers and matrix multiplication routines.",
diff --git a/tests/test_functional.py b/tests/test_functional.py
index 14cc21e..fcfdc72 100644
--- a/tests/test_functional.py
+++ b/tests/test_functional.py
@@ -1815,14 +1815,14 @@ def test_spmm_coo_dequant(dim1, dim2, dtype):
 batch_size = 1
 seqdim = 1
 values = []
-#values.append((batch_size, seqdim, 768, 4 * 768))
+values.append((batch_size, seqdim, 768, 4 * 768))
 # values.append((batch_size, seqdim, 1024, 4*1024))
 # values.append((batch_size, seqdim, 1536, 4*1536))
 # values.append((batch_size, seqdim, 2048, 4*2048))
 # values.append((batch_size, seqdim, 2560, 4*2560))
 # values.append((batch_size, seqdim, 4096, 4*4096))
 # values.append((batch_size, seqdim, 5140, 4*5140))
-values.append((batch_size, seqdim, 12288, 4*12288))
+#values.append((batch_size, seqdim, 12288, 4*12288))
 names = [
     "batch_{0}_seq_{1}_model_{2}_hidden_{3}".format(*vals) for vals in values
 ]
@@ -2125,3 +2125,26 @@ def test_extract_outliers():
         assert outliers2.shape[1] == idx.numel()
 
         torch.testing.assert_allclose(outliers1, outliers2)
+
+
+
+def test_blockwise_cpu_large():
+    diffs = []
+    reldiffs = []
+    batch = 128
+    seq = 128
+    for hidden in [128, 14336]:
+        for blocksize in [4096, 16384]:
+            for i in range(2):
+                A1 = torch.randn(batch, seq, hidden, device='cpu')
+                t0 = time.time()
+                C, S = F.quantize_blockwise(A1, blocksize=blocksize)
+                A2 = F.dequantize_blockwise(C, S, blocksize=blocksize)
+                print(time.time() - t0)
+                diff = torch.abs(A1 - A2)
+                reldiff = diff / torch.abs(A1 + 1e-8)
+                diffs.append(diff.mean().item())
+                reldiffs.append(reldiff.mean().item())
+                assert diffs[-1] < 0.011
+            # print(sum(diffs)/len(diffs))
+            # print(sum(reldiffs)/len(reldiffs))