Move perf funcs to perf folder

CliMA · Sep 25, 2023 · ca97b43 · ca97b43
1 parent 69ce863
commit ca97b43
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Showing 8 changed files with 54 additions and 44 deletions.
diff --git a/perf/benchmark.jl b/perf/benchmark.jl
@@ -1,7 +1,8 @@
 import Random
 Random.seed!(1234)
 import ClimaAtmos as CA
-config = CA.AtmosCoveragePerfConfig()
+include("common.jl")
+config = AtmosCoveragePerfConfig()
 integrator = CA.get_integrator(config)
 
 (; parsed_args) = config

diff --git a/perf/common.jl b/perf/common.jl
@@ -0,0 +1,32 @@
+"""
+    AtmosCoveragePerfConfig()
+    AtmosCoveragePerfConfig(; config_dict)
+
+Creates a model configuration that covers many physics components.
+
+The configuration precedence is as follows:
+1. Configuration from the given config file/dict (highest precedence)
+2. Default perf configuration (to increase coverage)
+3. Default configuration (lowest precedence)
+"""
+function AtmosCoveragePerfConfig(; config_dict = CA.default_config_dict())
+    perf_defaults = joinpath(
+        dirname(@__FILE__),
+        "..",
+        "config",
+        "default_configs",
+        "default_perf.yml",
+    )
+    perf_default_config = YAML.load_file(perf_defaults)
+    config_dict = merge(perf_default_config, config_dict)
+    return AtmosConfig(; config_dict)
+end
+
+"""
+    AtmosTargetConfig()
+    AtmosTargetConfig(; target_job)
+
+Creates an AtmosConfig given the job ID (target_job).
+"""
+AtmosTargetConfig(; target_job) =
+    AtmosConfig(; config_dict = CA.config_from_target_job(target_job))
diff --git a/perf/flame.jl b/perf/flame.jl
@@ -1,7 +1,8 @@
 import Random
 Random.seed!(1234)
 import ClimaAtmos as CA
-config = CA.AtmosCoveragePerfConfig()
+include("common.jl")
+config = AtmosCoveragePerfConfig()
 integrator = CA.get_integrator(config)
 
 # The callbacks flame graph is very expensive, so only do 2 steps.

diff --git a/perf/inference_flame_init.jl b/perf/inference_flame_init.jl
@@ -1,7 +1,8 @@
 import Random
 Random.seed!(1234)
 import ClimaAtmos as CA
-config = CA.AtmosCoveragePerfConfig()
+include("common.jl")
+config = AtmosCoveragePerfConfig()
 # To revive, define `args_integrator(::AtmosConfig)` and use that here
 integrator = CA.get_integrator(config)
 

diff --git a/perf/jet.jl b/perf/jet.jl
@@ -1,9 +1,8 @@
 import Random
 Random.seed!(1234)
 import ClimaAtmos as CA
-config = CA.AtmosCoveragePerfConfig(;
-    config_dict = CA.config_from_target_job("edmfx_adv_test_box"),
-)
+include("common.jl")
+config = CA.AtmosTargetConfig(; target_job = "edmfx_adv_test_box")
 integrator = CA.get_integrator(config)
 
 import JET

diff --git a/perf/jet_test_nfailures.jl b/perf/jet_test_nfailures.jl
@@ -1,7 +1,8 @@
 import Random
 Random.seed!(1234)
 import ClimaAtmos as CA
-config = CA.AtmosCoveragePerfConfig()
+include("common.jl")
+config = AtmosCoveragePerfConfig()
 integrator = CA.get_integrator(config)
 
 import JET

diff --git a/src/solver/solve.jl b/src/solver/solve.jl
@@ -89,7 +89,8 @@ Then, to run interactively:
 import ClimaAtmos as CA
 import Random
 Random.seed!(1234)
-config = CA.AtmosCoveragePerfConfig();
+include("common.jl")
+config = AtmosCoveragePerfConfig();
 integrator = CA.get_integrator(config);
 Y₀ = deepcopy(integrator.u);
 CA.benchmark_step!(integrator, Y₀);

diff --git a/src/solver/types.jl b/src/solver/types.jl
@@ -389,42 +389,6 @@ struct AtmosConfig{FT, TD, PA, C}
     comms_ctx::C
 end
 
-"""
-    AtmosCoveragePerfConfig()
-    AtmosCoveragePerfConfig(; s, config_dict)
-Creates a model configuration for many performance tests.
-Creates a config from the following in order of top priority to last:
-1. Configuration from the given config file/dict
-2. Default perf configuration
-3. Target job configuration
-4. Default configuration
-"""
-function AtmosCoveragePerfConfig(;
-    s = argparse_settings(),
-    config_dict = nothing,
-)
-    parsed_args = parse_commandline(s)
-    if isnothing(config_dict)
-        config_dict = YAML.load_file(parsed_args["config_file"])
-    end
-    target_job_config = if haskey(config_dict, "target_job")
-        config_from_target_job(config_dict["target_job"])
-    else
-        Dict()
-    end
-    perf_defaults = joinpath(
-        dirname(@__FILE__),
-        "..",
-        "..",
-        "config",
-        "default_configs",
-        "default_perf.yml",
-    )
-    perf_default_config = YAML.load_file(perf_defaults)
-    config_dict = merge(target_job_config, perf_default_config, config_dict)
-    return AtmosConfig(; s, config_dict)
-end
-
 function AtmosConfig(;
     s = argparse_settings(),
     parsed_args = parse_commandline(s),
@@ -439,6 +403,16 @@ function AtmosConfig(;
         @info "Using default configuration"
         default_config_dict()
     end
+    return AtmosConfig(config; comms_ctx)
+end
+
+"""
+    AtmosConfig(config::Dict; comms_ctx = nothing)
+
+Creates an AtmosConfig given the `config` Dict and kwargs:
+ - `comms_ctx` (optional) ClimaComms context.
+"""
+function AtmosConfig(config::Dict; comms_ctx = nothing)
     FT = config["FLOAT_TYPE"] == "Float64" ? Float64 : Float32
     toml_dict = CP.create_toml_dict(
         FT;