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tjake · Aug 26, 2024 · 36d9640 · 36d9640
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diff --git a/jlama-cli/src/main/java/com/github/tjake/jlama/cli/commands/ApiServiceCommand.java b/jlama-cli/src/main/java/com/github/tjake/jlama/cli/commands/ApiServiceCommand.java
@@ -15,24 +15,24 @@
  */
 package com.github.tjake.jlama.cli.commands;
 
+import static com.github.tjake.jlama.model.ModelSupport.loadModel;
+
 import com.github.tjake.jlama.model.AbstractModel;
+import java.util.Optional;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 import org.springframework.boot.SpringBootConfiguration;
 import org.springframework.boot.autoconfigure.SpringBootApplication;
-
 import org.springframework.boot.builder.SpringApplicationBuilder;
 import org.springframework.context.annotation.Bean;
 import org.springframework.context.annotation.Configuration;
 import org.springframework.web.servlet.config.annotation.ResourceHandlerRegistry;
 import org.springframework.web.servlet.config.annotation.WebMvcConfigurer;
 import picocli.CommandLine;
 
-import java.util.Optional;
-
-import static com.github.tjake.jlama.model.ModelSupport.loadModel;
-
-@CommandLine.Command(name = "restapi", description = "Starts a openai compatible rest api for interacting with this model")
+@CommandLine.Command(
+        name = "restapi",
+        description = "Starts a openai compatible rest api for interacting with this model")
 @SpringBootApplication(scanBasePackages = {"com.github.tjake.jlama.net.openai", "com.github.tjake.jlama.cli.commands"})
 @SpringBootConfiguration
 @Configuration
@@ -54,8 +54,7 @@ public AbstractModel getModelBean() {
 
     @Override
     public void addResourceHandlers(ResourceHandlerRegistry registry) {
-        registry.addResourceHandler("/ui/**")
-                .addResourceLocations("classpath:/static/ui/");
+        registry.addResourceHandler("/ui/**").addResourceLocations("classpath:/static/ui/");
     }
 
     @Override
@@ -74,9 +73,7 @@ public void run() {
 
             new SpringApplicationBuilder(ApiServiceCommand.class)
                     .lazyInitialization(true)
-                    .properties(
-                            "server.port", ""+port,
-                            "logging.level.org.springframework.web", "debug")
+                    .properties("server.port", "" + port, "logging.level.org.springframework.web", "debug")
                     .build()
                     .run();
         } catch (Exception e) {

diff --git a/jlama-cli/src/main/java/com/github/tjake/jlama/cli/commands/ClusterCoordinatorCommand.java b/jlama-cli/src/main/java/com/github/tjake/jlama/cli/commands/ClusterCoordinatorCommand.java
@@ -15,8 +15,6 @@
  */
 package com.github.tjake.jlama.cli.commands;
 
-
-
 import com.github.tjake.jlama.net.Coordinator;
 import picocli.CommandLine;
 

diff --git a/jlama-core/src/main/java/com/github/tjake/jlama/math/VectorMath.java b/jlama-core/src/main/java/com/github/tjake/jlama/math/VectorMath.java
@@ -32,9 +32,7 @@ public class VectorMath {
     public static void pfor(int start, int end, IntConsumer action) {
         PhysicalCoreExecutor.instance
                 .get()
-                .execute(() -> IntStream.range(start, end)
-                        .parallel()
-                        .forEach(action));
+                .execute(() -> IntStream.range(start, end).parallel().forEach(action));
     }
 
     public static void pchunk(int offset, int length, BiIntConsumer action) {

diff --git a/jlama-core/src/main/java/com/github/tjake/jlama/model/AbstractModel.java b/jlama-core/src/main/java/com/github/tjake/jlama/model/AbstractModel.java
@@ -15,6 +15,8 @@
  */
 package com.github.tjake.jlama.model;
 
+import static com.github.tjake.jlama.util.DebugSupport.debug;
+
 import com.github.tjake.jlama.math.VectorMath;
 import com.github.tjake.jlama.model.functions.EmbedInput;
 import com.github.tjake.jlama.model.functions.Generator;
@@ -45,8 +47,6 @@
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 
-import static com.github.tjake.jlama.util.DebugSupport.debug;
-
 public abstract class AbstractModel implements Generator {
     private static final Logger logger = LoggerFactory.getLogger(AbstractModel.class);
 

diff --git a/jlama-core/src/main/java/com/github/tjake/jlama/model/CausalSelfAttention.java b/jlama-core/src/main/java/com/github/tjake/jlama/model/CausalSelfAttention.java
@@ -15,20 +15,16 @@
  */
 package com.github.tjake.jlama.model;
 
+import static com.github.tjake.jlama.util.DebugSupport.debug;
+
 import com.github.tjake.jlama.math.VectorMath;
 import com.github.tjake.jlama.safetensors.Config;
-import com.github.tjake.jlama.safetensors.DType;
 import com.github.tjake.jlama.tensor.AbstractTensor;
-import com.github.tjake.jlama.tensor.BFloat16BufferTensor;
-import com.github.tjake.jlama.tensor.FloatBufferTensor;
-import com.github.tjake.jlama.tensor.operations.TensorOperations;
 import com.github.tjake.jlama.tensor.operations.TensorOperationsProvider;
 import com.google.common.base.Preconditions;
 import java.util.*;
 import java.util.function.Consumer;
 
-import static com.github.tjake.jlama.util.DebugSupport.debug;
-
 public class CausalSelfAttention {
     private final AbstractModel m;
     private final Config c;
@@ -257,8 +253,7 @@ public AbstractTensor forward(
                             int offset = h * c.headSize;
 
                             // skip if we are out of bounds
-                            if (offset >= query.shape().last())
-                                break;
+                            if (offset >= query.shape().last()) break;
 
                             int goffset = c.maybeMapToGroupHead(h) * c.headSize;
                             // rotate q by the freq theta and freq r
@@ -276,8 +271,7 @@ public AbstractTensor forward(
                         for (int h = c.groupHeadStart(); h < c.groupHeadEnd(); h++) {
                             // get the k vectors for this head
                             int offset = h * c.headSize;
-                            if (offset >= key.shape().last())
-                                break;
+                            if (offset >= key.shape().last()) break;
                             // rotate k by the freq theta and freq r
                             for (int i = offset; i < (offset + headPiece); i++) {
                                 float k00 = key.get(0, i);
@@ -314,15 +308,13 @@ public AbstractTensor forward(
                     debug("key+rope", key, finalPostion);
                 });
 
-
                 // Attention
                 VectorMath.pfor(c.headStart(), c.headEnd(), h -> {
                     try (AbstractTensor attn = m.makeFullTensor(1, kvp.shape().first())) {
                         int xoffset = c.maybeMapToGroupHead(h) * c.headSize;
                         int yoffset = h * c.headSize;
 
-                        if (yoffset >= query.shape().last())
-                            return;
+                        if (yoffset >= query.shape().last()) return;
 
                         // compute attention scores by multiplying query and key for every position
                         TensorOperationsProvider.get()

diff --git a/jlama-core/src/main/java/com/github/tjake/jlama/model/TransformerBlock.java b/jlama-core/src/main/java/com/github/tjake/jlama/model/TransformerBlock.java
@@ -15,20 +15,18 @@
  */
 package com.github.tjake.jlama.model;
 
+import static com.github.tjake.jlama.util.DebugSupport.debug;
+
 import com.github.tjake.jlama.model.functions.FeedForward;
 import com.github.tjake.jlama.tensor.AbstractTensor;
 import com.github.tjake.jlama.tensor.operations.TensorOperationsProvider;
-import com.github.tjake.jlama.util.DebugSupport;
 import com.github.tjake.jlama.util.Pair;
-import org.slf4j.Logger;
-import org.slf4j.LoggerFactory;
-
 import java.util.List;
 import java.util.Optional;
 import java.util.function.BiFunction;
 import java.util.function.Consumer;
-
-import static com.github.tjake.jlama.util.DebugSupport.debug;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
 
 public class TransformerBlock {
 
@@ -94,7 +92,6 @@ public AbstractTensor forward(
         AbstractTensor lnemb =
                 preAttentionNorm.map(ln -> ln.forward(embedding, normReducer)).orElse(embedding);
 
-
         debug("ln_emb", lnemb, layerIndex);
 
         AbstractTensor postAttention;

diff --git a/jlama-core/src/main/java/com/github/tjake/jlama/model/bert/BertConfig.java b/jlama-core/src/main/java/com/github/tjake/jlama/model/bert/BertConfig.java
@@ -19,7 +19,6 @@
 import com.fasterxml.jackson.annotation.JsonProperty;
 import com.github.tjake.jlama.math.ActivationFunction;
 import com.github.tjake.jlama.safetensors.Config;
-
 import java.util.List;
 
 public class BertConfig extends Config {

diff --git a/jlama-core/src/main/java/com/github/tjake/jlama/model/gemma/GemmaConfig.java b/jlama-core/src/main/java/com/github/tjake/jlama/model/gemma/GemmaConfig.java
@@ -19,7 +19,6 @@
 import com.fasterxml.jackson.annotation.JsonProperty;
 import com.github.tjake.jlama.math.ActivationFunction;
 import com.github.tjake.jlama.safetensors.Config;
-
 import java.util.List;
 import java.util.Map;
 

diff --git a/jlama-core/src/main/java/com/github/tjake/jlama/model/gemma/GemmaModel.java b/jlama-core/src/main/java/com/github/tjake/jlama/model/gemma/GemmaModel.java
@@ -97,7 +97,8 @@ protected TransformerBlock[] loadTransformerBlockWeights() {
                     weights.load(prefix + "up_proj.weight", c.offset()).quantize(qType)); // w3
 
             transformerBlocks[i] = new TransformerBlock(
-                    this, i,
+                    this,
+                    i,
                     new RMSNorm(
                             this,
                             weights.load(base + "input_layernorm.weight", c.offset())

diff --git a/jlama-core/src/main/java/com/github/tjake/jlama/model/gpt2/GPT2Config.java b/jlama-core/src/main/java/com/github/tjake/jlama/model/gpt2/GPT2Config.java
@@ -19,7 +19,6 @@
 import com.fasterxml.jackson.annotation.JsonProperty;
 import com.github.tjake.jlama.math.ActivationFunction;
 import com.github.tjake.jlama.safetensors.Config;
-
 import java.util.List;
 
 public class GPT2Config extends Config {

diff --git a/jlama-core/src/main/java/com/github/tjake/jlama/model/gpt2/GPT2Tokenizer.java b/jlama-core/src/main/java/com/github/tjake/jlama/model/gpt2/GPT2Tokenizer.java
@@ -18,13 +18,12 @@
 import com.github.tjake.jlama.safetensors.tokenizer.BPETokenizer;
 import com.google.common.collect.BiMap;
 import com.google.common.collect.HashBiMap;
-import net.fellbaum.jemoji.EmojiManager;
-
 import java.nio.charset.StandardCharsets;
 import java.nio.file.Path;
 import java.util.Map;
 import java.util.Optional;
 import java.util.stream.Collectors;
+import net.fellbaum.jemoji.EmojiManager;
 
 public class GPT2Tokenizer extends BPETokenizer {
 

diff --git a/jlama-core/src/main/java/com/github/tjake/jlama/model/llama/LlamaConfig.java b/jlama-core/src/main/java/com/github/tjake/jlama/model/llama/LlamaConfig.java
@@ -19,7 +19,6 @@
 import com.fasterxml.jackson.annotation.JsonProperty;
 import com.github.tjake.jlama.math.ActivationFunction;
 import com.github.tjake.jlama.safetensors.Config;
-
 import java.util.List;
 import java.util.Map;
 
@@ -53,6 +52,8 @@ public LlamaConfig(
                 eosToken instanceof List<?> ? (List<Integer>) eosToken : List.of((Integer) eosToken),
                 activationFunction,
                 ropeFreqsTheta == null ? 10000.0 : ropeFreqsTheta,
-                ropeScaling == null || !("linear".equals(ropeScaling.get("rope_type"))) ? 1.0 : Double.parseDouble(ropeScaling.get("factor")));
+                ropeScaling == null || !("linear".equals(ropeScaling.get("rope_type")))
+                        ? 1.0
+                        : Double.parseDouble(ropeScaling.get("factor")));
     }
 }
diff --git a/jlama-core/src/main/java/com/github/tjake/jlama/model/llama/LlamaModel.java b/jlama-core/src/main/java/com/github/tjake/jlama/model/llama/LlamaModel.java
@@ -70,7 +70,6 @@ protected EmbedInput loadInputWeights() {
                 at = TensorOperationsProvider.get()
                         .quantize(at, embedding.dType(), c.embeddingSegmentStart(), c.embeddingSegmentLength());
 
-
             embedding.copyFrom(
                     at,
                     at.getOffset(0, c.embeddingSegmentStart()),
@@ -110,7 +109,8 @@ protected TransformerBlock[] loadTransformerBlockWeights() {
                     weights.load(prefix + "up_proj.weight", c.offset()).quantize(qType)); // w3
 
             transformerBlocks[i] = new TransformerBlock(
-                    this, i,
+                    this,
+                    i,
                     new RMSNorm(
                             this,
                             weights.load(base + "input_layernorm.weight", c.offset())

diff --git a/jlama-core/src/main/java/com/github/tjake/jlama/model/llama/LlamaTokenizer.java b/jlama-core/src/main/java/com/github/tjake/jlama/model/llama/LlamaTokenizer.java
@@ -27,7 +27,8 @@ public class LlamaTokenizer extends BPETokenizer {
 
     public LlamaTokenizer(Path modelRoot) {
         super(modelRoot);
-        this.byteFallbackEncodingOffset = this.getModel().vocabLookup.getOrDefault("<0x00>", 0L).intValue();
+        this.byteFallbackEncodingOffset =
+                this.getModel().vocabLookup.getOrDefault("<0x00>", 0L).intValue();
     }
 
     @Override

diff --git a/jlama-core/src/main/java/com/github/tjake/jlama/model/mistral/MistralConfig.java b/jlama-core/src/main/java/com/github/tjake/jlama/model/mistral/MistralConfig.java
@@ -19,7 +19,6 @@
 import com.fasterxml.jackson.annotation.JsonProperty;
 import com.github.tjake.jlama.math.ActivationFunction;
 import com.github.tjake.jlama.safetensors.Config;
-
 import java.util.List;
 
 public class MistralConfig extends Config {

diff --git a/jlama-core/src/main/java/com/github/tjake/jlama/model/mixtral/MixtralConfig.java b/jlama-core/src/main/java/com/github/tjake/jlama/model/mixtral/MixtralConfig.java
@@ -19,7 +19,6 @@
 import com.fasterxml.jackson.annotation.JsonProperty;
 import com.github.tjake.jlama.math.ActivationFunction;
 import com.github.tjake.jlama.safetensors.Config;
-
 import java.util.List;
 
 public class MixtralConfig extends Config {

diff --git a/jlama-core/src/main/java/com/github/tjake/jlama/model/mixtral/MixtralModel.java b/jlama-core/src/main/java/com/github/tjake/jlama/model/mixtral/MixtralModel.java
@@ -98,7 +98,8 @@ protected TransformerBlock[] loadTransformerBlockWeights() {
                     expertUpWeights); // w3
 
             transformerBlocks[i] = new TransformerBlock(
-                    this, i,
+                    this,
+                    i,
                     new RMSNorm(
                             this,
                             weights.load(base + "input_layernorm.weight", c.offset())

diff --git a/jlama-core/src/main/java/com/github/tjake/jlama/safetensors/Config.java b/jlama-core/src/main/java/com/github/tjake/jlama/safetensors/Config.java
@@ -59,7 +59,6 @@ public class Config {
 
     public final TensorCache tensorCache;
 
-
     public Config(
             int contextLength,
             int embeddingLength,
@@ -125,10 +124,7 @@ public Config(
         this.ropeFreqs = ropeFreqsTheta == null
                 ? Optional.empty()
                 : Optional.of(VectorMath.precomputeFreqsCis(
-                        headSize,
-                        contextLength,
-                        ropeFreqsTheta,
-                        ropeScalingFactor == null ? 1.0 : ropeScalingFactor));
+                        headSize, contextLength, ropeFreqsTheta, ropeScalingFactor == null ? 1.0 : ropeScalingFactor));
 
         // Set default values
         setOffset(null);

diff --git a/jlama-core/src/main/java/com/github/tjake/jlama/safetensors/prompt/Function.java b/jlama-core/src/main/java/com/github/tjake/jlama/safetensors/prompt/Function.java
@@ -1,12 +1,24 @@
+/*
+ * Copyright 2024 T Jake Luciani
+ *
+ * The Jlama Project licenses this file to you under the Apache License,
+ * version 2.0 (the "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at:
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
+ * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
+ * License for the specific language governing permissions and limitations
+ * under the License.
+ */
 package com.github.tjake.jlama.safetensors.prompt;
 
 import com.fasterxml.jackson.annotation.JsonPropertyOrder;
 import com.google.common.base.Preconditions;
 import com.google.common.collect.ImmutableMap;
 import com.hubspot.jinjava.objects.collections.PyMap;
-
-import javax.annotation.concurrent.Immutable;
-import java.util.HashMap;
 import java.util.Map;
 
 /**
@@ -61,7 +73,11 @@ public Function build() {
     }
 
     private Function(String name, String description, Parameters parameters) {
-        super(ImmutableMap.<String,Object>builder().put(JSON_PROPERTY_NAME, name).put(JSON_PROPERTY_DESCRIPTION, description).put(JSON_PROPERTY_PARAMETERS, parameters).build());
+        super(ImmutableMap.<String, Object>builder()
+                .put(JSON_PROPERTY_NAME, name)
+                .put(JSON_PROPERTY_DESCRIPTION, description)
+                .put(JSON_PROPERTY_PARAMETERS, parameters)
+                .build());
         this.name = name;
         this.description = description;
         this.parameters = parameters;